SMA

A social structure made up of a set of social actors (such as individuals or organizations), a series of dyadic links, and other social interactions between actors.

1971 - ARPANET: transfer messages from one node to another of the network - made up of computers located in different US universities

1973 - Bulletin Board Systems (BBS): Computers that use software to allow external users to connect to them via the telephone line, giving the possibility to use centralized messaging and file sharing functions

1988 - Internet Relay Chat (IRC): is an instant messaging protocol on the Internet --> forerunner of instant messenger

1990 - Birth of WWW

1997 - SixDegrees: has main features of modern social networks 

2003 - MySpace: Most important social media until 2006, which introduced the ability to customize the graphic appearance of each user profile and to share music and videos  

2004 - Facebook

2006 - Twitter

Today - Insta, TikTok, WhatsApp

Blogs: discussion of certain topic, cronological order

Microblogging plattforms: small content in short text messages with multimedia (e.g. Twitter)

Forms/Discussion: diverse and specialized communities, extensive comment sections, and focus on facilitating in-depth conversations. Asynchronous communication (e.g. Q&A Tools, Reddit)

News sites

Social Networking sites (e.g. Facebook, LinkedIn)

Virtual game worlds (e.g. World of Warcraft)

Virtual social worlds (e.g. SecondLife)

Collaborative projects (e.g. Wikipedia)

Content communities: exchange multimedia content (Instagram, Snap, YT, etc.)

Individual content:

• Articles (mainly news)
• Posts (blog and social networking like FB)
• Micrologging content (short messages with multimedia)
• Reviews (e.g. Appstores, hotels, restaurants --> can take place on the site itself where purchase was made or on blogs and other social media)

Collective content:

• Threads: conversation between multiple users on topic proposed by user, which can last for years

Multimedia content:

• Images and videos: Been driving the market since 2016. Includes Stories, GIFs/Memes as well as vertical videos.

• Accessibility: access is easy and usually free ("extra" services may require special tariff plans, governments can restrict access to platforms)
• Global audience: the opportunity to communicate directly and simply with a global audience, so that the message (if well conveyed) can be amplified by contact networks
• Usability: anyone, regardless of the level of education or training, is able to publish and retrieve a considerable amount of information (with different levels of detail)
• Permanence: once created, the contents can be deleted, but depending on the type of platform used they can remain the property of that platform or remain accessible as "digital traces" even for a long time (is it possible to be “forgotten”? → Lesson on privacy)
• Speed: it is possible to access the information in real-time mode, in the very moment in which it was published
• Measurability: unlike traditional media, everything that can be found online is potentially measurable: comments, responses, reactions, likes, frequency in the use of words, etc.

In a  Decentralized Online Social Network (DOSN), there is no single service provider but a set of nodes that cooperate to guarantee all the functionalities offered by a centralized OSN.

Decentralization gives several benefits in terms of privacy ⇒ There is no central entity having control on users’ data or changes the existing terms of service, and this gives to the users more control over their data.

• How to guarantee the availability of social data, in an environment characterized by a high level of dynamism
• How develop techniques for propagating social updates in an efficient way
• Even if data is no more stored on centralized servers, new privacy issues have to be solved, for instance detecting trusted nodes that may host the pro-file of off-line users

Employing blockchain technology for different purposes, such as:

• To decentralize control on social data, in some cases letting users maintain control of their social content
• For introducing a rewarding system

Advantages:

1. Data control and content management
2. Censorship and democratized governance ⇒ Users can set their own rules for censorship and governance
3. Content originality and authenticity
4. User reward strategies

Disadvantages:

1. Scalability issues: May struggle to keep up with the demands of a mainstream social media platform (high number of users and transactions) 
2. Complexity
3. Transaction costs --> Users may need to pay transaction fees to perform actions on the blockchain, such as posting or interacting with content 

Example: Steemit

The measurement, collection, analysis and reporting of Web data for the purposes of understanding and optimizing Web usage

Social (Media) Analytics is monitoring, analyzing, measuring and interpreting digital interactions and relationships of people, topics, ideas and content. Interactions occur in workplace and external-facing communities

Internal tools:

• Facebook Insights
• Twitter Analytics
• Instagram Insights
• LinkedIn Analytics

External tools:

• Open-source software and related libraries for data analysis, representation, and visualization
  • R and Python libraries
  • Gephi
• Open-source and proprietary tools for data analysis, representation, and visualization
  • Neo4j
  • Tableau

Technological networks: man-made networks that are designed for the distribution of goods, resources, services ⇒ Internet, power-grid, telephone, shipping and distribution, etc.

Information networks: man-made networks made up of data and information linked together in some way ⇒ WWW (pages are nodes, hyperlinks are edges), email comm. networks or citation networks

Biological networks: interaction patterns between biological elements ⇒ neural networks or ecological networks

Social networks: People or groups are nodes, interaction between them are edges ⇒ Friendship and knowledge networks, Meme spreading, Collaboration charts, Disease transmission, etc.

• Algebraic representation
• Graphical representation
• Matrix representation
• List representation 

Original tool to graphically represent the configuration of social relations within a group.

Euler formulated the the problem of the bridges of Königsberg using a graph

He found out that it is not possible to take a walk-in order to cross all the bridges once and only once? 

Instead, it is possible:

• If the number of incident arcs in each node is even (there are 0 nodes with odd number of incident arcs)
• Or if only two nodes have an odd number of incident edges
• Solution is to add an extra bridge. 

1. G = (V,E) such that E ⊆ [V]² ⇒ The elements of V are the vertices (or nodes or points) of the graph G, the elements of E are its edges (or arcs)
2. V(G) = {v₁, v₂, … , v_n}
3. E(G) = {e₁, e₂, … , e_m} ⇒ e is denoted always denoted as a pair e = (a,b)

1. V(G) = {1, 2, 3, 4, 5, 6, 7}
2. E(G) = {{1, 2},{1, 5},{2, 5},{3, 4},{5, 7}} 

1. |G| = |V(G)| = n
2. ||G|| = |E(G)| = m

Directed: Edges have orientation(from one vertex to another) 

Undirected: Edges are undirected, bidirectional

1. a,b are called the extreme vertices of e
2. e is called the incident edge (arco incidente) in a and b
3. a,b are called adjacent vertices (vertici adiacenti)
4. a is called neighbor of b in G and vice versa

Set of vertices adjacent to v1 = N_G(1) = N(1) = {2, 3}

Set of edges incident to v3 = s_G(3) = s(3) = {(1,3), (3,4), (3,5)}

1. e is called outgoing edge (arco uscente) from a (tail vertex/vertice coda)
2. e is called ingoing edge (arco entrante) in b (head vertex/vertice testa)
3. a is said to be direct predecessor (predecessore diretto) of b
4. s is said to be the direct successor (successore diretto) of a

1. E⁺(5) = {(3,5), (4,5)}
2. E^-(2) = {(0,2), (1,2)} 
3. Only incoming edges, Sink Vertex: 4
4. Only outgoing edges, Source Vertex: 0

If a graph G has no loops and no multiple edges (multiple edges between same vertices), G is called a simple graph.

1.  The number of edges incident to a node (equivalent to saying that it is the number of neighbors of a node) 
2. |E(v)| = d_G(v) = d(v) 
3. They are counted twice
4. isolated vertex
5. d(a) = 5, d(e) = 0

1. minimum degree = δ(G) = min{d(v)|v ∈ V} 
2. maximum degree = Δ(G) = max{d(v)|v ∈ V} 
3. δ(G) = 0, Δ(G) = 5

1 x Summe aller Degrees aller Vertices geteilt durch die Anzahl Vertices in einem Graph (|V|)

The sum of all degrees of a Graph can be easily calculated by multiplying the number of Edges X 2. 

1. 4
2. 5
3. 2
4. 5
5. 4