Social Media Quiz 2

Network Ties

Undirected: family ties Directed: advice relations (has an arrow)

What is social network analysis?

A set of research methods for identifying structures in systems based on the patterns of relations among system components, offer almost an MRI image of an organization Gartner group called it an "untapped information asset" In communication, the relations usually refer to the amount of information exchange among components In other social sciences, it may refer to power, advice, conflict, friendship, cognitive, stimuli, joint activities, shared affiliations, disease, material or workflows

A typology of ties

A tie can be from similarities, social relations, interactions, and flows. Similarities could be location, membership, attributes Social relations could be kinship, other role, affective (likes/dislikes), cognitive (knows/knows about) Interactions could be anything Flows (information, beliefs, personnel, resources)

Types of networks

Adjacency (one-mode) networks Affiliation (two-mode) networks

Star Topology

Each of the nodes are connected to a central node with a point to point link fashion, like a hub and spoke fashion (the central node is the hub and the outer nodes are the spokes) All data transmitted between nodes has to go through the central node first, and then is retransmitted out

What is graph theory?

Graph theory is where you represent a social network as a graph that depicts relations between objects It helps you understand a complex system and how its components interact with each other

Matrix Network

If the graph was weighted, it will have numbers showing that The matrix is the graph that marks if A talked to C, etc; All the names are listed on the top and on the side, the amount of interactions are then counted from there

Network Components

Node (vertex), link (tie, relation, edge), hub, network

Dissemination rate

Percentage. Absolute unique visitors x home country visit rate/population in the country 2010

Home country visit rate

Percentage. Portion of the visits from the same country as the national website

New visit rate

Percentage. The share of the new visitors of total visits

Edge List Network

Shows the relations between people, if there are repeats then you write their name twice, Maria to SPark, Maria to Gabe, etc; Vertex 1 and Vertex 2

Network positions

Star, liaison, bridge, gatekeeper, isolate

Keywords

The keywords that were used when the website was accessed via a search engine result page

Edge Attributes

Weight: frequency of communication Ranking: best friend, second best friend... Type: friend, relative, co-worker Properties depending on the structure of the reset of the graph: betweenness

Tree Topology

a central "root" node (the top level of the hierarchy) is connected to one or more other nodes that are one level lower in the hierarchy (i.e., the second level) with a point-to-point link between each of the second level nodes and the top level central "root" node the top central node is the only one without other nodes above it the hierarchy of the tree is symmetrical, each node in the network having a specific fixed number, f, of nodes connected to it at the next lower level in the hierarchy, the number, f, being referred to as the "branching factor" of the hierarchical tree.

Network

a complex interconnected group or system

Link (tie, relation, edge)

a connection between parts in a network

New visitor

a new visitor is a visit by a visitor who has not been recorded previously. A high number of new visitors indicates strong visitors recruitment

Hub

a point in a network that connects many nodes to each other

Node (Vertex)

a point in a network where points connect or cross

Returning visitor

a returning visitor is a visit by a visitor who has been recorded previously. A high number of return visitors suggests that the website content is engaging enough for visitors to come back

Bus Topology

all nodes are connected to a common transmission medium which has exactly two endpoints (this the bus, which is commonly referred to as the backbone or trunk) all data that is transmitted has to be over the single line, so virtually all nodes receive the data simultaneously

Bridge

an actor or edge linking two or more groups (strict definitions may require that no other link between the two groups exist)

Liaison

an actor that has links to two or more groups that would otherwise not be linked, but is not a member of either group

Isolate

an actor who has no links to other actors

Star

an actor who is highly central, has many connections

Gatekeeper

an actor who is in the position to mediate or control the flow between two parts of the network

Calculating Closeness Centrality

based on the length of the average shortest path between a node and all other nodes in the network

Bounce rate

bounce rate is the percentage of visits that come to a website and leave it without continuing to other subpages. Bounce rate is a measure of visit quality and a high bounce rate generally indicates that site entrance (landing) pages are not relevant to visitors

Hybrid Topology

composed of one or more interconnections of two or more networks that are based upon the other network typologies we already discussed

Adjacency Networks

consists of a single type of nodes and the links between them (friendship networks, it is a one way street, someone likes another person more)

Brokerage

control over bridging two nodes together

Ring Topology

each node is connected to two other nodes in the network, with the first and last nodes being connected to each other, forming a ring all data transmitted travels from one node to the next in a circular manner, generally flowing in a single direction

Mesh Topology

each of the nodes of the network is connected to every single other node, if you want to transmit data then it would be transmitted to every single other node simultaneously

Unique visitor

estimated number of people who visited the website Visitors and users are different, you could have 10 visits but only 1 user who visited 10 times

Affiliation Networks

have two types of nodes, often called actors and events (employer-employee)

Closeness Centrality

how easily a node can connect with other nodes the closer you are to people, the easier it is to connect. minimal effort to connect with your neighbors, vs a larger effort to connect with people far from you the value of closeness is the ease of connection: the shorter the distance between you and another node, the fewer network hops you have to make

Betweenness

identifying the role of "bridge" measures the number of times the node acts as a bridge along the shortest path between two other nodes in a network how many pairs of individuals would have to go through you in order to reach one another in the minimum number of hops

Different centrality measurements

indegree, outdegree, betweenness, closeness

Page views

page views is the total number of pages viewed on the website and is a general measure of how much the website is used

Returning rate

percentage. The share of returning visitors from total visits

Density

the actual number of connections in a network expressed as a proportion of the total possible number of connections a figure between 0 and 1 not easy to make meaningful comparisons of density across networks of different sizes (or different relation types) high density should generate greater: trust, cultural homogeneity, and diffusion speed

Average time on site

the average time of all users time on the website

Betweenness Centrality

the degree to which a node forms a bridge or critical link between other nodes the value of betweenness is the power you have to block or grant access to others the more nodes that depend on you to make connections for them, the greater your potential value to them and thus your power

Degree Centrality

the number of connections a node has to other nodes, the value of a high degree is potential potential: the potential to connect and interact with a great number of other nodes in the network Undirected graph: a count of the number of unique edges connected to it Directed graph: can be both indegree and outdegree

Indegree

the number of edges that point towards the vertex of interest (number of people that have invited that person to the party)

Outdegree

the number of edges that the vertex of interest points towards (number of people that person has invited to the party)

Depth of visit

the number of page views of one visitor per visit. The depth of visit is a measure of visit quality. A large number of high page views per visit suggests that visitors interact extensively with the website.

Visitor loyalty

the number of the repeated visits by returning visitors. Loyal visitors are usually highly engaged with the brand of the website and high number of multiple visits indicates a good customer and visitor retention

Visits

the number of visits the measured website receives is the most basic measure of how effectively the website is promoted

Time on site

the time a visitor spends on site. One way of measuring the visit quality. If visitors spend a long time visiting the website, they may be interacting extensively with it. However, time on site can be misleading because visitors often leave browser windows open when they are not actually viewing or using the website

Landing pages

the web page on a website where the visitor "lands" first, i/e/ the web pages which the visitor meets first when entering the website

Direct traffic

visits from people who clicked a bookmark to come to the website or who type the websites URL directly into their browser

Search engines

visits from people who clicked a link to the measured website on a search engine result page

Referring sites

visits from people who clicked a link to the measured website on another website

Network Centrality

which nodes are most central, who is influential in shaping the discussion, the definition varies based on the situation local measure: degree relative to the rest of the network: closeness, betweenness, eigenvector, katz, pagerank how evenly is centrality distributed among nodes: centralization, hubs and authorities

Closure

with three nodes, A B C, if AB have a connection and BC have a connection, it is likely that AC will have a connection