SOCIAL NETWORKS

Cognitive consistency theory

Whom members think other group-members like

Is Hierarchy of Positions in a Corporation a Social Network?

Yes because there are people involved, even though there are weak ties. BUT it is not the same as the structure showing an ego and his/her alters **All it takes is people and how they are connected..which can be defined in many different ways

Gladwell "Tipping Points": Stickiness Factor

You need an idea that will stick... not just go in one ear out the other. Also about the merit of the disease that makes it stick e.g. HIV virus has been around for at least a century but in the 80s it was an epidemic.. the virus mutated in a certain way so that it became "sticky" and was very hard to get ride of

Sociometry

a way to map the social network and is a technique for eliciting and graphically representing individuals' subjective feelings toward one another The links in the social network provided channels for the flow of social influence and ideas among the girls → it was their location in the social network that determined whether and when they ran away

Clusters/communities

groups

Degree Centrality:

hHow many ties touch a node? • Directed Networks o Indegree of A: 2 • A lot of ties come to you o Outdegree of A: 1 • Socialable you go to ties? • Undirected Networks o Degree of A: 3 o Degree of B: 2 • the social role is important too because...? o The role that you portray based on indegrees and outdegrees

Small world problem:

if two persons are selected at random from a population, what are the chances that they would know each other, and more generally, how long a chain of acquaintanceship would be required to link them In population like US, 50% of pairs could be linked by chains with no more than 2 intermediaries -This led to Milgram's popular notion of "six degrees of separation"

Path

lengths (steps needed to take to connect -- sequence of edges/connections

Nodal Centrality

measures different ways that a node is "connected" to others in the network. Helps us understand the flow of how resources move in a network and the flow of influence in a network *different centrality measures answer different questions about the nodes in a network

Diversity of Networks in the Modern Age of ICTs

why is diversity in our networks important? -general internet use allows us to have more diverse social networks- it's not just the use of SNS hat does this, it's everything internet related, including emails and web surfing

Gudrais 2010: Networked-->Ex 3: Health Information Spread

• Bogart: Spread of HIV conspiracy beliefs • Dangerous, as they increase risky behavior, reduce treatment, and thus increase contagion • Effect of opinion leaders in specific HIV communities •We believe we are independent actors, but are embedded in networks of social influence •Ideas of diseases- ex/ vaccination causes autism; people who believe this engage in behaviors that makes the situation worse

network

•measure of the network •the # of possible ties that actually exist compared to the number of possible ties that don't exist -not individual network -some netowrks are more interconnected than others depending on the number of the nodes •Directed Networks ~# actual ties / (n°(n-1)) ~where n = # of nodes •Undirected Networks ~# actual ties / (n°(n-1))/2 ~where n # of nodes the denser the network → the easier it is to share information** easier to get things done → information is shared more easily o less dense networks ?

Disrupting Scale-Free Networks

The breakdown of a substantial number of nodes will result in a network's inevitable fragmentation: This is true for a RANDOM NETWORK because if you take out random nodes in a scale-free network, they are much more likely to be "not-so-well connected" types --Scale-free networks are very hard to disrupt... except, if you target the Hubs (aka the Achilles' heel of scale-free networks) which it is not easy to do-- you have to identify them first

Nodes and Links

The only two components of a network --NODES (verticies, actors) are entities (e.g., corporations, countries, words in a book, people) connected to each other by LINKS (connections, ties, edges) -- the relationship and however you want to define it- knows, loves, does business with) -Actors denote human and non-human actors, and in a network take the shape that they do by virtue of their relations with one another More nodes and links= more possible configurations Innumerable possibilities for what a node and link can represent (a word, a gene, a person, phonetic similarity, etc.)

Networks: No Agency Required

The study of networks is about WHERE we are in relation to others and what that means about our access to resources, our ability to influence others, our ability to control others- not so much about our actions, but rather our potential to take action (I could potentially ask this resource-rich person for help)

Collective Action Theory

The theory that explains how people coordinate their efforts to secure a common goal that one could obtain without the efforts of others - Results in some "public good" - physical goods like parks, bridges, or libraries; intangible goods like databases of information or communication systems

Media Multiplexitiy

The use of multiple forms of media to communicate with a certain type of person in order to get a resource

Affiliation network matrix

They are two mode networks that allow one to study the dual perspectives of the actors and the events (unlike one mode networks which focus on only one of them at a time Provide conditions that facilitate the formation of pairwise ties between actors. They also enable to model the relationship between actors and events

Do Structural Holes=Weak Ties?

They may start that way, but they are much more than just weak ties... Weak Tie= a description of "closeness" between two nodes, a predictor of certain types of resources one can get from others- considers informational benefits Structural Hole= the gap between two groups that can be exploited; considers control benefits; can be a weak tie at first BUT it can evolve over time

Strong Ties

Ties between two people who interact often and recently, interact with emotional intensity, interact with ease, are intimate and mutually confide, share a base of trust , can help reduce uncertainty to one another and can provide comfort to one another --Family relationships --Mentor relationship --Close friendships --Spouses/romantic partners --to lesser extents, neighbors and work relationships **strong ties are inherent in many social networks, they are key to giving us support in our lives and are key to our general well being, some are static, but many are not

Balance theory

To explain how individual attempt to structure their relations with others to avoid emotional or cognitive dissonance A way to explain social pressures "Locally balanced but fragmented"

Multiplexity

Two different types of relationship with the same person (your boyfriend but you also work together). Higher multiplexity usually means more closeness

2 kinds of networks:

Two kinds of networks: •Directed Networks (asymmetrical): --> arrow at one end ~network in which the tie has direction (aka digraphs) ~EX: hitting, kissing, selling drugs, infecting someone, sending a letter; having an affair w/ some1 who doesn't know u exist •Undirected Networks (symmetrical): networks in which connections/ties have no direction (arrow at both ends)

Types of Centrality

Types of Centrality 1. Closeness Centrality: 1/farness -farness: sum of the steps (geodesic) to each node ....add em together (ex: 1+1+2+3+1) 2. Degree Centrality: Degree = number of links. More degrees = more important 3. Betweenness Centrality: How much a node relies on other nodes for a thing -if a node has high betweenness centrality, then they are a broker that many other nodes have to go thru

What is a Social Network?

"A social network is a set of relations among network members-be they people, organizations or nations...everyone is embedded in structures of relationships that provide opportunities, constrains, coalitions, and work-arounds. Society...is made out of a tangle of networked individuals." (Rainie, Lee and Wellman) The Social Network Revolution: "It is important to realize that the social network revolution came first- before the internet revolution or the mobile revolution." (Lee and Wellman)

Kadushin and Social Capital

"As social networkers hope, these connections can be useful. Connections have the potential to give a perosn access to valuable sources such as: referral to jobs by people out of one's immediate circle who might know of jobs one's close friends are unaware of; ability to rise in the social ladder of occupations; help with personal problems; referral to a good restaurant, book, movie; or someone who can pick up your mail when you are away. These networked resources that you do not know, but to which you have access through your friends and acquaintances are called 'social captal'"

Six Degrees of Separation

"In the 6 degrees of separation not all degrees are equal" (Gladwell) "There appear to be highly popular channels for transmission of the chain" (Milgram) --More than half of all the Milgram letters arrived to the target through only 3 people --Any person anywhere can be contacted by any other person in a few steps, unless one of them is a complete and total hermit THE PATTERN EMERGES: "Six degrees of separation doesn't simply mean that everyone is linked to everyone else in just six steps. It means that a very small number of people are linked to everyone else in a few steps, and the rest of us are linked to the world through those few." (Gladwell, pg. 6)

Heider's Balance Hypothesis

"In the case of three entities a balance state exists if all three relations are positive in all respects, or if two are negative and one is positive" (Kadushin p.23) --There are 16 possible configurations of triads

Influencers vs. Influenced

"large cascades of influence are driven not by influential but by a critical mass of easily influenced individuals."

Degree

# of connections a node has

What Makes an Epidemic?

(noun): a widespread occurrence of an infectious disease in a community at a particular time

*Video: Social Capital and Technology

- Bonding report more overall social support and specifically more emotional support and companionship - But, photo sharing and activities online increase social capital indirectly - Social media use can directly and indirectly relate to higher levels of bridging social capital

Is Online Privacy a Guarantee in the Modern Age?

- Privacy is a right enshrined by the Privacy Act of 1974: "no agency shall disclose any record which is contained in a system of record by any means of communication to any person, or to another agency, except pursuant to a written request by, or with the prior written consent of, the individual to whom the record pertains." -BUT, the law provides for 12 exceptions! includes provisions for the FIA, Bureau of Census (Takes info on population demographics), anonymous data, requests from law enforcement, congress and court orders -Just because it is a right doesn't mean that SNS providers will always give us that right! Governments will not be dissuaded to deny/change these rights - Users can check their behavior online: some evidence that younger users are being more careful, or at least more aware of their online behavior - users can change default settings on SNS, including how they want their data stores and shared with third paries

What Networks are NOT Good at When it Comes to Activism- according to Gladwell...

- Reaching consensus - Setting goals - Thinking strategically - Avoiding Conflict and Error - Taking on a powerful and organized establishment

ICTs Allow for "Glocalization"

- There is a duality in how ICTs influence social relations. They support relationships both globally and locally -ICTs allow social participation that is both unbounded from shared time (i.e. global) and geography and tied to local activity -Hampton calls this "glocalization"

Kang Kim Gloor Bock - Understanding the effect of social networks on user behaviors in community-driven knowledge services

- This study examines the impact of the overall structure and the dyadic strength of social networks on the quality of answers of CKSs for answering ties, co-answering ties, and getting answers ties. Community-driven Knowledge Services = CKSs - CKSs are online communities where users ask and answer questions. o Examples: Yahoo! Answers (US) and Naver Knowledge (South Korea) - From a social network perspective: o CKSs involve more types of social relationships than do traditional informational sites with little interaction among users. Relational and structural network tie influences on quality of answers provided to online knowledge site

Three categorizations of social relationships at CKSs:

- Three categorizations of social relationships at CKSs: 1.Answering ties 2.Co-answering ties 3.Getting answers ties Background Background - CKSs o User asks a question o Other users begin to submit answers o Asker chooses "best" answer o Question moves to "resolved database" o CKSs rewards "knowledge points" to knowledge contributors based on their answering performances

Why Is Network Density Important?

- if the network is not dense, many people are susceptible to "activation"; but the propagation (spread of beliefs) of influence is installed - if the network is very dense, people need multiple "active neighbors" to be "activated" themsleves - Global "cascades of influence" take place in-between "not dense" and "very dense" networks

Use of Online SN Sites

- in 2005, before Facebook, only 8% of adults used SNS, today that number is 75% (every 3 out of 4 people in America use SNS)- all adult internet users make up about 86% in 2016. It's plateauing now..unique situation for people in their 20s because it has happened over our lifetime - Females use it more (68% in 2015) compares to males (62%) -Platform: 76% of online adults use Facebook, followed by Insta, Pinterest, LinkedIn, Twitter and so on -Facebook is most popular all over the world!! -68% of all Americans use Facebook -A lot of people who make under 50k a year claim that they use Facebook- maybe this is because they're younger -32% of online adults use Instagram- maybe a gap with adults and young people because of selfie phenomenon and privacy issue -31% of online adults use Pinterest- gender divide, women use this a lot more - Not all SNS are the same thing, and scholars have a hard time pinning down what exactly a SNS is, and social media, and is one thing the other thing?! -It comes down to how we define these things -29% of online adults use LinkedIn- mostly used by those with a college degree and people who make over 75K -24% of online adults use Twitter

Network Density

- measure how many links are in the network - divide that by the maximum number of potential links that the network could have - the maximum number depends on how many nodes a network has - for n nodes, the max number of links is n(n-1)/2 for a network with undirected links; n(n-1) for a network with directed links ^EX: 9 links total, 7 nodes: (7)(6)/2=21 so density= 9/21=0.428

Whole-Network Measures

- network density: the most popular whole-network measure - measures how may links there are relative to the size of the network - a measure of network cohesion - other measures include network reciprocity, network diversity, network transitivity

Social Networking Sites Allow People To:

- present themselves with a public/semi public profile - articulate a list of other users as their social network - view their connections within the system - establish and maintain connections with other users (old and new) - American users grown exponentially in just the last 10 years - regardless of what these websites were originally oriented towards, their purposes are elastic and change as people's uses of them evolve

Communication Networks

- the patterns of contact that are created by the flow of messages among communicators through time and space - can take many forms in organizations: personal contact networks, flows of info within and between groups (intra-organizational) and strategic alliances among organizations (inter-organizations)

Degree Centrality

- the simplest and most popular centrality measure - measures how many links are at node x - if the links are undirected (A---B) then the degree centrality is the sum of all links at a node - if the links are directed (A--->B) we classify them as "incoming" or "outgoing"- measures are In-Degree Centrality or Out-Degree Centrality examples: - if all blue nodes have one link attached to them its 1 degree centrality. if five links are attached to the green node its 5 degree centrality -in-degree centrality of A is three and in-degree centrality of B is 3, 2 out-degree centrality for G *look on GauchoSpace for these!!

How do Networks In Organizations Evolve?

- they can emerge from the ground-up: reductionism, the structure emerges from the people and their personal characteristics - from the top-down: holism, the structure is everything: people's personal characteristics aren't - by leaning on existing environmental/external structures: construction, there's a co-dependency between both structure and people - ways people have started to think about organizations and networks

Networks as Conduits for Influence

--"Networks are conduits of both wanted and unwanted flows" (Kadushin)-- meaning that connected people tend to have an affect on one another and this affect can be positive or negative, but the fact that you are connected inevitably has an influence --TedTalk: All imbedded in these social networks and how they affect our lives- social networks are so elaborate and complex, that one should ask what is their purpose?

Structural Holes' Connection With Weak Ties

--Burt's theory builds on Granovetter's theory of the role of weak ties as important resource bridges- weak ties are very similar to these structural holes --But he always focuses on the role of strong ties- people can only maintain so many strong ties; eventually, they have to reach out via bridges, but these bridges are so valuable, that the relationships have the be maintained...hence, a weak tie could turn into a strong tie and we could still call it a bridge!

Networks As Information Maps

--Diagram of books bought by the same people in 2008 presidential campaign: this tells us that people read all kinds of books but despite this seemingly random phenomenon of people buys all sorts of books all the time, they cluster around ideologies (reflecting homophily-love of the same thing) --A typical social network structure showing an "ego" and his/her "alters": many subcultures within one large society- some you are close with peripherally, don't share many connections with them; others you are physically close to and similar to--this is a map, it shows you how to get to a side --Human relationships are not random and in fact, that reveals itself when you map out your connections with people

Affective Characters of Strong Ties

--Emotional intensity --Intimacy --Stress-free environment --Harmony --No tension *very subjective

Causes of Homophily

--Geographical Propinquity (closeness/proximity) --Family Ties --Organizational Ties --Isomorphic Positions (socio-economic background) --Cognitive Processes (shared knowledge, easier to communicate with that person and to share cultural tastes and other things that make a relationship homophylous)

Second Class Exercise

--Higher numbers indicate a more diverse close-knit group, which brings social benefits. The higher the number, the more social capital one has with close ties --Higher numbers indicate a more diverse support group, which brings social benefits. Could be seen as a social capital measure **Correlative measures: --0 (not correlated at all) to 1 (they're measuring the same thing) Correlation of Q4 to Q6- 0.25 Correlation of Q4 to Q5- 0.12 Correlation of Q6 to Q5- 0.04 --The answers to Q4, 5 and 6 are not too highly correlated- it suggests we're measuring different things with these different questions

Barabasi's Experiment

--In the late 1990s, Barabasi and his colleagues collected huge amounts of data on the WWW (which was enormous by that point) --Expected to find hyper-linked documents randomly connected, because people follow their unique interests when deciding what sites to link their Web documents to --People's interests are very diverse and there are many pages to choose from on WWW SO, the pattern should be "fairly random".... BUT IT WASN'T: a few highly connected pages are essentially holding the WWW together --More than 80% of pages have less than 4 links and less than .01% of pages have greater than 1,000 links (call these "hubs") --It seemed that the probability for a Web page to have k links was in the realm of 1/k squared or 1/k cubed (that's not a bell curve). If you pick up a web page randomly on the Internet and wanted to know the probability of that page having a large amount of connections, turns out that probability is tiny because most web pages on the Internet have a small amount of links --Visually, most social networks look like scale-free ones

Social Networks and New Media

--Information and Communication Technologies (ICTs) --Mediated communication (the effect of the "in-between"- that being technology) **Network ideas are useful for displaying data such as who bought what book but are especially helpful in making sense of news that involved connections, such as who was involved in what banking deal, who was tied to Madoff's Ponzi scheme, or who was in the network of 9/11 hijackers. Newspapers and Web news sites increasingly use them. Displays of networks on the Web are especially useful because they can be interactive, allowing further information about the points in the network --Online media (like Reddit) makes it easy for someone to put ideas out there and spark debates- about access to different information, but little to do with making friends --There are hypotheses out there that says we can't overload ourselves with over 160 friends (like on Facebook) --We apply classification schemes on what we want to know

Marriage and Strong Ties

--Kalmijun (2003) article: how marriage influences social networks? says there is a dyadic withdrawal --How do we (North Americans) see collective vs. individuals? small and tight networks vs. large and separated networks --Joint social networks are a form of marital capital- this means that exit costs of marriage are higher than any other relationship because both spouses tend to lose more friends after a divorce if they have most of their friends in common

Individuals' Consequences of Not Having Enough Weak Ties

--People with "few weak ties will be deprived of info from distant parts of the social system and will be confined to the provincial news and views of their close friends. This deprivation will not only insulate them from the latest ideas and fashions but may put them in a disadvantaged position in the labor market" --"Such individuals may be difficult to organize or integrate into political movements of any kind, since membership in movements or goal-oriented organizations typically results from being recruited by friends." --"Without weak ties, (any social/political action) momentum does not spread beyond the clique" --Social systems lacking in weak ties will handicap: new ideas, scientific endeavors, consensus and shared living between groups separated by race, ethnicity, geography or other characteristics

Random Networks that Didn't Exist

--Traditionally, complex networks thought to be random (Etdos-Renyl model from 1956; simple model, elegant mathematics) --Found NOT to be realistic in a LOT of real-world cases- especially for social networks because of HOMOPHILY --The random model predicted a deeply democratic system --Most nodes would have approximately the same number of links --One node would be, more or less, as influential as the next one

Class Exercise-Gladwell's Results with 3 Groups (Taken in 2002)

--You looked at a list of 250 surnames taken from a diverse place (Manhattan NYC) and gave yourself a point for every person you knew with that last name OUR RESULTS: Avg= 36.9, Range- 3-83 Most Students= 20-29 GLADWELL'S RESULTS: 1) Undergrad students Av. Score= 21 Range=2-95 --many of them recent immigrants, many of the middle and lower income families 2) Health educators Av. Score= 39 Range=16-108 --many of them in their 40s and 50s --many of them highly educated and wealthy 3) His random fiends Av. Score=41 Range= 9-118 --many of them in their late 20s and 30s --many of them professionals

SN Sites and the News

-About 6 in 10 Americans get news from social media -Reddit-70% of users, Facebook- 66% of users, Twitter- 59% of users -64% get news on just one site, 10% of users get news on three or more sites

Stanley Milgram: The Milgram Small World Experiment

-American social psychologist -Chose random participants in Omaha and Wichita and one random target person in Boston...asked how many intermediaries between them? -Sent packets to his participants- each had a letter to send to the target: Basic info about the target, but not the address **RESULTS: It took anywhere between 1 and 11 intermediaries, but the vast majority took 5 to 6..this was a surprising finding at the time- the first time this concept was tested

What Can Social Networks Help Explain?

-Health trends like the spread of diseases (or bad habits) -Psychological affects (happiness, loneliness, depression) -Behavior (how people find jobs, get married, get divorced) "Its not what just what you know, its also who you know."

Why are Social Networks Are More Persistent Now?

-ICTs allow for relationship maintenance and reduce the likelihood that ties will ever become completely dormant -In the past, networks of old ties were abandoned with marriage or moving - But now, the content of the relation's messages remain persistent over time - Hampton and colleagues find that this directly benefits network diversity and access to social capital

The Case of Kitty Genovese

-Kitty Genovese was attacked and killed in 1964 in NYC in broad daylight- her attack was witnessed by 38 neighbors but no one called the police - Why do we have this bystander problem? is it because people are jaded in big cities?

Granovetter's Theory on the Strength of Weak Ties

-Originally (in the early 1970s) he was looking for how people found their jobs and kept encountering the answer that it was through an acquaintance, not a friend -Whatever resource is to be diffused, it can reach a larger number of people and transverse greater social distance when passed through weak ties, rather than strong ties -The "strength of weak ties" is that they provide connections to others outside the strong tie network (along with their new resourceS) -Weak ties can help someone generate creative ideas, find a job, get info on the competition, etc. -Weak ties require less time, less energy and fewer overall costs to maintain, which releases time to do other things (we can relate this to our habits of social networking online)

Social Networking Sites and Neighborhoods

-SNS give us higher levels of network diversity overall, btu less diversity in the neighborhood setting -this is consistent with historical trends of newly adopted communication technologies like the telephone -SNS allow people to more easily access social support from outside the neighborhood setting, so it reduces reliance on neighborhood/local ties

Why are Social Networks More Pervasive Now?

-Social networks are more visible today than before because of their online contexts -We are more aware of our "friends" and their activities today-"Pervasive Awareness"- the other times when we had this phenomenon in society is when we lived in closely-tied villages

Downsides to the Persistence and Pervasiveness of SNs

-The existence of network diversity doesn't guarantee that social capital will remain accessible - This visibility could lead to increased network closure: --> meaning that our ties to outside networks weaken to the point that we don't get new information -->leads to a decline in bridging social capital - could ultimately reduce trust, tolerance, opinion, quality and competitive advantages- SILO EFFECT

How are Networks Descriptive?

-Who's "well-connected" (and who cares)? -Who's isolated? -Who's an effective bridge?

Diffusion Curve

-a model for a self-limiting contagious process - number of people affected, influences and time -an S curve -Applies to the diffusion of epidemic diseases, innovative technology use, new ideas, gossip -In a short time, triggering event ("tipping point") happens here and saturation point is reached

Online Messaging Communication

-among smartphone owners.. 29% messaging apps 24% auto-delete apps and 5% anonymous apps

Eigenvector Centrality

-answers the criticism of degree centrality -a more sophisticated version of degree centrality -idea is that a node is important if it is linked to by other important nodes -like degree centrality, it calculates the number of links on a given node- but then each adjacent node is weighed by its own centrality- so, a link to a high-centrality node "counts for more" -popular in measuring influence and access to influential nodes in a network- the Google search algorithm uses a variation on this measure to decide how "important" a webpage is

FACEBOOK USERS

-are more trusting than others -have more close relationships -get more social support than other people -are more much more politically engaged than most people -FB revive's 'dormant' relationships -SNS are increasingly used to keep up with close social ties -Myspace users are more likely to be open to opposing points of view -women and the young drive FB usage -SNS users have more friends and more close friends (average American has 634 ties in their overall network on average) -About half of FB users' overall network is connected on FB

Factors Affecting Organizational Networks

-info and comm technologies - globalization - "the networked society" - ties closely with info and society - all of these defy boundaries set by social tradition, nations and institutions

Relationship Networks in an Organization

-managers can be more effective if they utilize network analysis on 3 types of relationship networks: *The Advice Network: who depends on who for advice? *The Trust Network: who shares delicate political information in a crisis? *The Communication Network: who talks about work-related maters most regularly?

Organizations: Networks Can Reveal Problems

-multiple networks in an organization may either be in-sync with each other or at odds -managers care about making them in-sync -communication patterns are key in revealing dysfunction: networks that don't communicate with others (or with only 1 other networks) or networks that only communicate with others -network analysis can reveal "holes"- places where you would expect to find relationship ties, but don't OR "bowties- places where many players are dependent on a single employee, but not on each other

Online Social Networking: A Brief History (pre 2000)

-social networking was present in early online services like AoL, prodigy, CompuServe- late 80s early 90s -with the creation of the WWW, online communities sprung up: examples- geocities, theglobe.com, TriPod, Classmates.com- early-late 90s -With the 2nd generation WWW (aka. web 2.0), social media and SNS really took off- web pages could be dynamic and highly multimedia (change content based on user inputs): for example- Friendster, Myspace, Cyworld, LinkedIn Okurt, early 2000s -The Facebook "explosion"-started off as just a site for college students in 2004, for everyone in 2006; led the way for many other SNS services like Twitter, Pinterest, Instagram, Foursquare, Snapchat, etc.

GUDRAIS -- Networked --Networks in Society --Network science

. Gudrais: Harvard network studies •Wide variety of network studies •Both common and unique network properties Obesity spreads through social networks -if your friend becomes fat, you have a higher chance of following suit (spreads thru up to 3 degrees of separation) **Proves that our health depends on both ourselves, and those we surround ourselves with. The study of networks can illustrate how viruses, opinions, and news spread from person to person and can make it possible to track spread of obesity, suicide, and back pain Network science points toward predicting stock-price trends, designing transportation systems, and detecting cancer Network science is unique in that physicists and molecular scientists work together with social scientists --> Interdisciplinary: physicists [work with big data], computer scientists, molecular biologists, humanists, social science Similar patterns for depression, alcohol, quitting smoking, even divorce (our health depends on more than our own biology or own choices and actions) Track what matters; ex. Proximity, familial relationships, etc. •Network influences on voting [how you vote; who you vote for], obesity, word memory, cancer cell position in cell network, stock prices, health [More friends you have, longer you live, and happier you are,] longevity [More friends you have, longer you live, and happier you are] •Polling, what you read in the press •Explanation of cancer- location that cancer cell is in the structure of cells (not just individual cells) o Some types of cancers spread faster depending on where they are in the network

Binary

0,1

How Do ICTs Affect Our Core Networks?

1) The "Alone Together View": ICTs displace face to face communication and cause our core networks to shrink. EX: when both of you are on your phones while together (Sherry Turkle and others) 2) The "Online-Mirrors-Offline" View: ICTs frequent use within core networks is associated with frequent face-to-face contact. EX: the more I communicate with my loved ones online, the more face-to-face contact I get with them (Keith Hampton) VIDEOS: *Turkle: the goldie locks effect- not too close, not too far, just right. but this can be harmful for adolescents who need to develop face to face relationships. Changing the way people think of themselves (I share therefore I am). We use technology to define ourselves by sharing our thoughts and feelings (I want to have a feeling, I need to send a text). If we don't have connection we don't feel like our selves, so we connect more and more but in the process set ourselves up to be isolated. If you don't cultivate the capacity for solitude, the ability to be separate. Solitude is where you find yourself so you can reach out to other people and create real attachments. -Technology Determinism: technology defines who we are and determines our future -Technology Constructionism: we construct these tools for certain purposes- feedback mechanism where these tools influence us but not from one extreme to the other. *Hampton: people more likely to spend time in more diverse groups, more groups less likely to be using mobile phones. social stress, awareness of problems of others, seems to be related to social media use. -->He presented his views differently than Turkle because he brought up more studies and his approach was a lot more nuanced - he's saying things are complicated and we are still trying to find out- but it looks like it's not all bad

Gladwell "Tipping Points": Law of the Few

80/20 principle- 20% of the population has 80% of the wealth

The Influentials Hypothesis (Watts and Dodd)

A central idea in marketing and diffusion research is that influentials—a minority of individuals who influence an exceptional number of their peers—are important to the formation of public opinion. - Found that anyone can start an influence cascade, but the network will either help or limit it - "Influentials" are those who are highly connected, but the cascades they trigger are only a little bigger than "non-influentials" - they are most effective when they are "early adopters" - Influencers are so, MOSTLY because of the places they occupy in their networks! they are not better informed, or wiser, or forward-looking than others, they are just better connected. -most social change is driven not by influentials but by easily influenced individuals influencing other easily influenced individuals.

Transitivity

A friend of a friend is likely to also be your friend- how cliques are formed

Adjacency Matrix:

A is connected to D and B but not to C 4 nodes, so a 4x4 matrix representation -An example of a sociogram -Shows who is next to whom, and represents relations of nodes -If something is adjacent to something else, that means it's near something else -Typically adjacency matrix is a 0 or 1 binary network -If I did not talk to thee, then 1 to 3 would be 0 -Contains rows, columns, diagonals, groups

Internet Social Capital Scales (ISCS)

A survey tool that asks people about their perceived access to resources from their social connections --Measures different dimensions, like community engagement (general reciprocity, access to resources therein); how well do people connect with a broad range of others; what close ties do people depend on or trust; how do people get to all manner of resources (both the low-cost and the high-cost types) --Meant to capture measures of BOTH bonding and bridging capital

Position Generator

A survey tool that asks people: do you know someone who is a police/officer/lawyer/teacher/mechanic..etc.? measure of actual access to resources --Reasoning: the more diverse people's full social network are, the more resources they have access to; measurement of access to social resources is useful in instrumental actions and it can reveal a way to measure certain bridging capital

Name Generator

A survey tool that asks people: who do you discuss important matters with? who do you rely on for help with everyday tasks? from whom could you borrow a large sum of money? --Reasoning: this tells us who you get your resources from and how many there are- a measurement of supportive exchanges hat have specific criteria- it can reveal a way to measure certain bonding capital

Binding (Borgatti)

A theoretical process Borgatti et al.: Networks and social science Historical, conceptual, & theoretical foundations of network analysis The binding mechanism is similar to the old concept of covalent bonding in chemistry. The idea is that social ties can bind nodes together in such a way as to construct a new entity whose properties can be different from those of its constituent elements. Binding is one of the mechanisms behind the popular notion of the performance benefits of "structural holes" Given an ego network (the set of nodes with direct ties to a focal node, called "ego," together with the set of ties among members of the ego network), a structural hole is the absence of a tie among a pair of nodes in the ego network

Directed Link

A------>B A is linked to B Examples: A votes for B, B doesn't vote for A; Following celebrities on Instagram or Twitter, they don't follow you back

Undirected Link

A-----B Simple link between two nodes Says nothing about directionality

Intermediary Link

A---->B---->C A is linked to C through B

Symmetrical Link

A<----->B A and B are linked together

Dyads and Mutuality (Reciprocity)

A<----->B is a dyad- a relationship between two people --Assumes a give-and-take relationship.. not true for any dyad though --Dyadic relationships are most likely to be reciprocal the closer the two people are (strong ties) --Reciprocation between dyads can be achieved even if the two nodes have fewer things in common- it can happen with weak ties also, but less often, and for different reasons

The Difference Between Structural Holes and Weak Ties

According to Burt: 1) weak tie is a description, whereas a structural hole is a "causal agent" 2) the weak tie argument talks about the informational benefits, but obscures the control benefits of structural holds **In order for you to know something new, you need to go beyond your strong ties, because they know what you know!

Closeness centrality

Actors directly or indirectly connect to the rest of the actors in the network

Balance, triads, and stability

Basic network building block is a triad** Makes things more complicated Direct and indirect; power imbalances; cognitive and emotional balance; Simmel: the "third" can be non-partisan, mediator, but also leverage relations to advantage (broker) Balance= Friend of my friend is my friend Imbalanced triad creates tension; if I give that person money Can generate irrationality Entirely balanced networks may not work well

Putnam's 2 Types of Social Capital

Bonding Social Capital: Allows access to resources from one's strong ties; usually associated with trustworthiness and social norms Bridging Social Capital: Accessed from outside the core network, comes via one's weak ties, and is usually associated with volunteering or acquiring new information or brokering activity

Brokers vs Connectors (Lee Flemming Study)

Broker: an influential person connected to many people who DON'T know each other Connectors: An influential person with a habit of introducing his collaborators to each other **brokers are more likely to come up with new ideas because all info flows thru them **but, Connectors have a much easier time getting publicized (due to their connectivity) *argues that noncompete clauses induce brain drain. Companies might lose their most productive inventors who like to collaborate with others and other companies

Gudrais 2010: Networked-->Ex 2: Networks & Innovation **Brokers vs Connectors (Lee Flemming Study)

Brokers vs Connectors (Lee Flemming Study) •Fleming: Does position in network influence inventor success? •Citations of patents, collaborations •Collaboration across many research centers increased innovation! -BROKER: an influential person connected to many people who DON'T know each other ~BROKER is a person who is in between groups. That person will have access to new groups and spread them, and connector is connected to people in diff groups -Want a broker and a connector in research groups -CONNECTORS: An influential person with a habit of introducing his collaborators to each other **Brokers are more likely to come up with new ideas because all info flows thru them **BUT, Connectors (introduce collaborators) have a much easier time getting publicized (due to their connectivity) *Argues that "non-compete" clauses induce brain drain --> limits innovation. Companies might lose their most productive inventors who like to collaborate with others and other companies •Ex/ find someone who goes to lots of conferences and someone shares those ideas

Burt's Ideas on Weak Ties

Burt followed up on Granovetter's work: People who connect to dense (but otherwise unconnected) groups together are: likely to be "weakly linked" individuals to one or both groups...like a tremendously powerful position..called these positions "structural holes."

Social Capital and Civic Engagement

Classical Theory on Social Capital: - communities succeed better at solving collective problems when they have greater stocks of social capital - civic organizations do best if they have networks of trust and reciprocity and repeated face-to-face engagement

How do We Study Networks in Organizations?

Classically, we can focus on one the 3 aspects of perspectives: 1) positional- how the position occupied by people influences communication 2) relational- how the quality of relationship between people influences communication- dominant perspective in comm studies 3) cultural- what cultural characteristics/norms/biases influence communication Although interesting and useful, these network traditions focus attention at a meta-theoretical level and fail to specify the theoretical mechanisms, such as self-interest, contagion, and exchange, which describe how people, groups, and organizations forge, maintain, and dissolve linkages.

Component

Clique

Classification of Networks: Socio-Centric Networks

Closed system networks (ex: the network of people who know each other in this class only)

Closeness Centrality

Closeness Centrality: = 1/Farness • centrality - how close you are at the center • Closeness centrality : how many steps does it take to get to each person? Add it all up and then (total number of steps it takes to get to each person) • farness of A = !+ 1 + 1 +2 + 3 = 8 o How close are you to the other person • Farness: Sum of distance

Causal direction of relation between common norms/values and common attributes

Common norms or values => bring nodes with similar attributes together Common attributes => develop common norms and values

Archival network data

Computer logs, telephone logs, and diaries Example: acebook has created a vast archive of social connectedness

Structural Holes

Consider two separate networks- if someone could close the separation between them, they could have a lot of power/influence; Burt called this separation a "structural hole" --Structural holes are of potentially high value if they are bridged by an arguably powerful broker who facilitates and controls the flow of information between people from opposite sides of the hole

Homophily and Silicon Valley

Cultivate ties to one another through their practice of regular licensing to one another and also exchanging personnel

Can We Measure Social Capital?

Debatable issue- because it's a complex social phenomena, a multi-dimensional concept and different measures exist and focus on different aspect --Putnam's "Bowling Alone" Concept: Similar measures to levels of social trust or participation in voluntary association --Some popular ways of measuring social capital include name generators, position generators, internet social capital scales (ISCS)

Bacon centrality

Degree centrality is the measure of the highest number of connections In social networks, this person is very well-connected The more someone has been around->connections-> the more connnections ----- -- -----This isn't enough.. Because you need different social circles

Affiliation matrix

Describes the groups, events, labels, nations, or actions (mode 1) with which nodes (mode 2) are affiliated. Example: All soccer fans have an affiliation relationship, similar in sense that you enjoy the same type of sport Think of the plants to animal example in class with butterflies, bees, other insects and types of plants they are affiliated with

What Are Networks? Who Studies Them?

Descriptions of the relationships between two or more entities. Can help explain and abstract complex phenomena. Examples: -How cells are linked together can help explain how some cancers are formed -How words and their meanings are linked together can help explain linguistic dynamics of languages -How documents on the web are linked together can help explain how people search for information online -How people are linked together can help explain why they play the roles that they do *Communication scholars, economists, anthropologists, sociologists, etc. all study networks

To Tech or Not to Tech?

Dunbar thinks technology has proven so far - his hypothesis is very popular with many others: "social brain hypothesis": big brains evolved to solve the problem of social life. Living in large groups confers significant advantages, chief amongthem better protection against predators. As brain size increases, so does group size , Facebook, path -The bigger the neocortex, the larger the group a primate could handle. At the same time, even the smartest primate—us—doesn't have the processing power to live in an infinitely large group. To come up with a predicted human group size, Dunbar plugged our neocortex ratio into his graph and got 147.8. -Dunbar claims that technologies that encourage co-presence (face to face communication) is better than those that don't (for ex: skype vs. e-mail) BUT.... not everyone agrees: -Duncan Watts (network research at MS research) believes our friendships are more than just close/not close. Relationships are specialized! -Dustin Moskovitz (facebook co-founder) driven by idea that "dunbar's number" can be increased via tech

Gudrais 2010: Networked-->Ex 1: Diffusion/Contagion

Ex 1: Diffusion/Contagion •More nodes, more links, more complexity, more emergence, more higher-level implications (more things to look at/more pieces of the puzzle) •Odd similarities across very different networks •Slime mold network more efficient finding shortest path than students o Slime mold generates particles and it senese where it's going and communicates that to other cells. Figure out where pathway is. Ants and bees do same thing, communicating to their networks. •Innovative and influential analysis of Framingham Health Study (data since 1948, 50,000 social ties among 5124 people, linked to more than 12,000 others) o Ask questions about health and life, tracking them thru their life o Ask them to name their three best friends oAt each time period when data was connected, saw 3 ppl named and found info for those three people about same things (health, longevity, and what they do) •Obesity (up to 3 degrees separation) •Happiness •Loneliness •Depression •Alcohol consumption •Smoking cessation o People who smoked became more clustered and more on the peripheral; smoking became less of a social norm •Divorce •Implications for vaccination (more central; actors linked from randomly selected nodes)

Connectors

Figures out how to reach people, even if not known Make the world work; spread information & ideas

Critical Mass

For diffusion of contagions, we need a critical mass: a minimum amount of something required to start or maintain a venture

Formal vs. Informal Organizations

Formal Organizations: the hierarchical relations in an organization (CEO on top, officers below him, manager below them, etc.)- defined by an organizational chart -Krackhard and Hanson say that we should actually pay more attention to the informal organization -Formal organizational structures do not capture the important aspects of communication in organizations -informal organizational structures can fill in the gaps in our understanding of communication in those environments - however.. no organization is ever either formal or informal --> there is a continuum that ranges from formal to informal --> there is a coexistence of the two networks- we use them for specific purposes, to become more formal when we want something done according to whatever bureaucratic rules we know, and informally to help reach the social way of doing things

Offline vs. Online Collective Action- Flanagin and Colleagues

Found that these phenomena do differ and there isn't enough theory to explain it yet.. including hybrid approaches (e.g. both online and offline civic engagement) *Modeling the Structure of Collective Actions: offer a 2-dimensional model of collective actions space with a communication perspective: (a) the mode of interpersonal interaction and (b) the mode of engagement that shapes interaction.

Theory of cognitive consistency

Friends were friends with one another (they labeled this "schema consistent") tended to be more satisfied than those whose friends did not get along with one another Whereas the theory of transactive memory focuses on what members think other group members know, cognitive consistency theory focuses on whom members think other group members like.

Normal Vs. Power- Law Distribution

Gaussian (Normal) Distribution: --examples: grades in a class or on the SATs, blood pressure measurements of humans, length of human hands Power Law Distribution: higher number of links, lower number of nodes --examples: word frequencies in language, document citations/ WWW links, distribution of wealth generation

Are Our Core SNs Smaller Today?

Generally, yes. But not because there's less support in society but because American society is relatively prosperous and formal resources are relatively abundant Technology doesn't cause this because Hampton and his colleagues argue that contact using ICTs supports larger core networks (except when formal resources are low)

Does Technology Make Us Communicate With Each Other (face to face) Less Often?

Hampton and colleagues found that frequent ICT use within core networks is associated with frequent face to face contact -exception: the most disadvantaged have higher face to face contact with core ties in absence of new communication technology- in this case, face to face contact is lower with ICT use

Mathematical Language and Social Networks

Helps quantify characteristics; a good tool to make comparisons with, set benchmarks with. We can thus measure node characteristics, link characteristics or whole-networks characteristics

Attributes

Homophily Causes: -Norms and Attributes ~Bring nodes with similar nodes together-> Develop common norms and values -Structural Location: ~This fosters similar behavior & attitudes ~Similarly also brings people to same location

The Power of Homophily

Homophily in these areas (and in this order) create the strongest divide in our personal environments-- but can't we make 'significant ties' with others who are unlike us? yes, but we need a common ground- we cannot always be emphasizing differences: 1) Race and Ethnicity 2) Age 3) Religion 4) Education 5) Occupation 6) Gender

Gladwell "Tipping Points": Power of Context

How we're sensitive to our environment

Homophily

If 2 people part of the same population share similar characteristic, they are more likely to connect

Balance: Friends and enemies

If A dislikes C and B dislikes C then A and B like each-other Theory of structural balance accumulates throughout system of relations

The Poole-Kotchen Model

If, on average, we know 500 people each, then, only 1 in 200,000 people (chosen at random) know each other- very mathematical and unrealistic with people! The odds drop dramatically if we also consider mutual acquaintances

Homophily: Birds of a Feather Flock Together

In social circles, people with similar taste in perspective or those who have more in common will tend to "flock together" or connect with one another --Why do we seek this? because it is familiar, relatable and easier- there is less of a barrier between you and someone else; for self-reassurance --BUT, we often take advantage of connections with others who we know superficially because they can offer us something new

Appicella Marlowe Fowler Christakis - Social networks and cooperation in hunter-gatherers

Katz - Network Theory and Small Groups:

Connections

Links, edges, or ties

Scale-Free Networks

Many "real-world" networks are dominated by a relatively small number of nodes that are highly-connected, compared to the rest- EX: World Wide Web (hyperlinks), cellular metabolic systems, hollywood actors, social networks -These highly connected nodes are often called **"HUBS", are described as "high degree" of connectedness, or "has a high number of connections", serve specific purposes in their networks

Leetaru 2017 Global News Story Network

Massive and GDELT Project All online news coverage (121,000,000 articles) Worldwide in 2016 Hyperlinks between those articles Via extraordinary visual document extraction

Betweenness centrality

Measure the times that a particular node is the member of the shortest path between two other nodes Low shortest average path between others; (intermediary, controlling or brokering flow) If between groups, then liaison or bridge

Betweenness Centrality

Measures how often a given node falls along the shortest path between two other nodes- how much of an intermediary is a certain node to others? *METHOD: - select a node to measure and call it the "focal node" - consider every pair of nodes in the network except for the focal nodes - calculate the ratio of those that pass through the focal ode to the total number --> A high betweenness centrality valued node in a network has a large potential for controlling flows through the networks. It can also tell us that the node can threaten the network with flow disruptions - Betweenness centrality is an effective way to demonstrate the small-world phenomenon (realistic networks, which are scale-free and very resilient)

Views on Network Structure are Meta-Theories & Just the Beginning

Monge & Contracter offer closer ways/angles/theories to look at that help explain organizational network dynamics: Self-Interest: social capital, structural holes Collective Action: the "public good"; how people take collective action and how these networks help or hinder that action; some companies encourage employees to be political activists Cognition: how we process knowledge, who in the org knows about this topic that I have to work on, knowing how you process knowledge and where you look for knowledge has a lot to do with how you think. Do orgs influence the way we think? yes! does the way we think influence orgs? maybe... Contagion: social learning- how we learn from others Exchange: resource exchange Homophily: social identity

Ties and the Support They Offer

Most relationships provide specialized support- the kinds of support that are related to characteristics of the relationship than to characteristics of the network members themselves. Strong ties with friends, neighbors and siblings make up half of all supportive relationships

Classification of Networks: Open System Networks

Networks in which the boundaries are not necessarily clear (ex: the network of people who buy wines online)

Networks in Organizations

Networks in workplaces - sports team, workplace, etc. -multi-layer nature

Classification of Networks: Ego Networks

Networks that are connected with a single individual (ex: your network of friends)

Criticism of Degree Centrality

Not adhering to a strict definition: it does not take into account any measures of the whole network beyond the adjacent nodes

Coleman's 3 Forms of Social Capital

Obligations/Expectations: Family or close friends will do everything for each other; usually not costly Information Channels: Getting informational resources through social relations; can be costly Social Norms: Social standards- allowing certain actions, but constraining others; often restrictive and very negotiable-- customary rules of behavior that coordinate our interactions with others.

Dunbar's Number

Our Brains, Our Lived (with others) -there is a cognitive limit to the number of people we can form close relationships with -our brain size sets this limi to 150 people for us -150- the new pi? the figure of 150 seems to represent the maximum number of individuals with whom we can have a genuine social relationship with, the kind of relationship that goes with knowing who they are and how they relate to us - It's a 2-fold reason: Time (expense) and Brain size (physiology/evolution) - Dunbar's research looked at several societal situations through human history- always found that the average was around 150 - why 150? dunbar thinks our development of language is key to expanding our close social circles to 150- others think his approach is too simplistic- what about other ecological factors like the need to forage or build defenses? others have found different numbers when using different methods of measurements... does technology help increase that number or does it just verify that limit?

Theory of Embeddedness

Over-socialization o People that are "overwhelmingly sensitive to the opinions of others and hence obedient to the dictates of consensually developed norms and values" (Granovetter, 1992). Under-socialization o Individual decision making is influenced by individual utility without any impact of social structure or relations. - The theory states that a person's social networks affect his or her behavior. o More specifically: Both dyadic relations with a counterpart (i.e., relational embeddedness) and the overall network of relations (i.e., structural embeddedness) influence human behavior.

Propinquity

People you are socially close to also tend to be living geographically close to you

Boase (2006): Networked Individualism

Rather than relying on a single community for social capital, individuals must actively seek out a variety of appropriate people and resources for different situations transformed communication from house-to-house to person-to-person, creating a new basis for community

Indirect links

Reachability are reduncanced

Social Capital

Refers to social networks and the associated norms of reciprocity (Putnam) --When two people are tied to one another in a social network, they exchange resources (material, money, goods, or non-material) --Social capital derives its value from being shared --It represents the potential for resource exchange --It is different from other types of capital because: it is the goodwill that is created by the fabric of social relations or the value of connections: Social "success" depends on social capital, and social success is contextual because it depends on your situation

The 2- Step Flow (Lazardsfeld and Katz)

Researched the influence of media on people in the 50s *theory: individuals may be influenced MORE by exposure to each other than to media- opinion leaders will act as intermediaries between media and everyone else

Rice - Using network concepts to clarify sources and mechanisms of social influence

Social Influence and Social Information Processing (SIP) in Organizations

Sociogram

Sociograms are a graphic representation of the social links between people or other entities. ... In NVivo, vertices are cases (or Twitter users in a Twitter sociogram). 2 Edge—represents a connection or interaction between vertices. In NVivo, edges are relationships

How are Strong Ties Related to Our Group/Community/Family Ties?

Strong support from our communities generally gives us a better way to get resources, interactions that go beyond narrow reciprocity, much of the social capital we need/use --People's community ties are not all homogenous, close by and densely connected...actually, they are usually socially diverse, spatially diverse and sparsely knit!

Small Change- Gladwell Article in the New Yorker (2010)

Synopsis: compares activism of the civil-rights movement in the 1960s with social media activism in 2010s; compares and contrasts "high risk" activism vs. "low-risk" activism Civil Rights Activism: HIGH RISK- hierarchical, strategic, precise, disciplined, not resilient if leaders are gone, Strong Tie Phenomenon, asks a lot of its participants, confronts socially entrenched norms Social Media Activism: LOW RISK- builds networks, very adaptable, resilient to being shut down, Weak Tie Phenomenon, lowers level of motivations for participants to take action, brings only social acknowledgement and praise

How do Scale-Free Networks Form?

THE MATTHEW EFFECT; Aka Accumulative Advantage: "The rich get richer and the poor get poorer"; From the "parable of the talents" in the New Testament (Matthew ch. 25) --Also sometimes referred to as: pareto distribution, 80/20 rules, Zipf distribution --Due to the growing nature of networks, older nodes have greater opportunities to acquire links --People reinforce a bias towards popularly linked nodes in a network: They will want to connect with those that are already highly connected (in this case, the 'hubs') rather than those that are not as highly connected.. which makes them grow. PREFERENTIAL ATTACHMENT **Growth + Preferential Attachment = Hubs in a Network

Phenomenological View of Networks

The Network (and its structure) <------> The Behavior of People: networks are both a cause and a consequence of human behavior

Does the Internet Help Build Social Capital or Harm It?

Is community life "disappearing" in the online social networking age? --Boarse et al says not- it is just being transformed (focuses on weak ties) --Duke study says yes, because Americans' "circle of confidants" has shrunk (focuses on strong ties)

Social Networks and Obesity

Is it really an epidemic? Degree of Separation of body size (increase in probability that a person is obese given that a social contact is obese)----> Induction (me gaining weight causes you to gain weight) or Homophily (we share a similar body size) or Confounding (we share a common exposure to something like a health thing) **FOUND EVIDENCE FOR ALL THESE THINGS, including induction (ex: lets go have muffins and beer- adopt that combination and start gaining weight like them OR they start gaining weight and it changes your idea of what an acceptable body size is)

Induced vs. Choice Homophily

Induced vs. Choice Homophily 1. Induced Homophily: a tendency for ties to form to similar others b/c similar others are especially present in the social environment (group, community, society). **tightly nit groups 2. Choice Homophily: A tendency to choose to form ties with similar others b/c we share similarities w/ them (clusters form)

The Helpful Side of Technology

Internet tools can help ensure "regular contact with large networks" because as the size of someone's social network increases, it becomes more difficult for someone to contact an individual in that network --1/3 of Americans say that the Internet has played an important role in helping them deal with at least one recent major life decision

Six Degrees of Lois Weisberg

Lived in Chicago and happened to know many people.. she was randomly in town at a park and there was commotion, she stopped to find out what was happening, got into a conversation with a random woman who she then invited over to her home/office and became friends with her. She introduced the woman to other people in Chicago, but claims that 80-90% of people she met in chicago were directly linked to Lois Weisberg. Even if they hadn't met so randomly in that park, chances are that the woman who was new to Chicago would have probably met Lois at some point or another, because Lois knows everyone --What gave her social power is that she knew so many people from so many different walks of life (musicians, artists, politicians, science fiction writers).. she liked being the connector between these people who had little connections with each other. She had a personality that loved having different people around --How does Gladwell tie her story into Milgram's "small world"? Because...Lois is one of those people who knows everyone, and so it would only take a few people to finally get to know her.. --Ties into Granovetter's "weak ties" because people find jobs through weak ties and Lois knew a lot of these people rom different circles, but wasn't necessarily best buddies with them. She could connect people through Lenny Bruce. Also structural holes, she was the bridge/facilitator/broker/controller between two separate groups which gave her a lot of social power.

Reciprocity

The extent to which people reciprocate each other's friendship..but this doesn't necessarily mean that the relationship is super close