Determinación del contenido de grasa

A social network is a social structure made by entities which are tied by some kind of interdependency or relation. Entities under study are usually individuals, but organizations, groups of individuals, or societies may also be analyzed within this perspective. The idea of social networks first appeared in the works of ´Emile Durkheim and Ferdinand T¨onnies back in the 1890s.

Although the study of social networks lays its foundations back in the late 1800s, online social networks as we understand them today did not appear until 1997, when sixdegrees.com was inaugurated. The original sixdegrees.com died long ago, but many others that followed its steps are now capturing everyone’s attention. Over time, OSNs functionalities have expanded incredibly, from simple places to upload content and share it with friends to crucial media to communicate. Games, chats, and photo albums were some of the elements quickly introduced in general purpose OSNs. Lately, many other features are starting to popularize inside these networks. For instance, location based services that make use of the geographical position of a user (usually obtained through the usage of a mobile device) to offer specific services. Moreover, some OSNs have also been gaining power as real-time sources of updated information from peers, challenging the traditional information flow model. Information can now be obtained from first hand experiencers and almost instantaneously.

Online social networks are web services that allow users to create a public (or partially public) profile describing some information about themselves and share information with other users of the network [22]. Their most characteristic feature is that they allow users to create explicit relationships between them in the network.

In general terms, joining an OSN consists of two basic steps. In the first place, users sign up by filling an online form with personal data that establishes the user’s profile. The visibility of this profile depends mostly on the OSN and, in second term, on users’ preferences. While some OSNs such as Tribe [23] or

Friendster [24] make profiles public by default and allow them to be indexed by search engines, other networks such as Facebook [25] or Flickr [26] let users configure their profiles’ visibility based on groups. Other OSNs like Last.fm [27] allow users to change the visibility of some of the attributes that the network stores while other OSNs like Twitter [28] do not provide such granularity and the profile only admits two protection levels: visible or private.

Once the profile has been created, users can start to establish explicit relation- ships with other users. There are many kinds of relations that a user can create in an online social network. “Friend”, “fan”, “contact”, or “follower” are the most popular ones. Apart from creating explicit relationships in the network, OSNs usually allow users to communicate or interact with each other.

Graphs that are used to represent users and their relationships are called social graphs; they have been widely used to analyze OSNs in a broad variety of studies.

2.2.1

Social graphs

A social graph is defined as a graph where nodes represent users in an OSN and edges denote links between them. Node attributes are then information about the user (such as age, gender, or sexual preferences) and edge attributes may be used to describe relationships. Edges may also have an associated weight, representing some quantity regarding the relationship. Depending on the kind of relationship expressed, social graphs can be seen as directed or undirected graphs. Social graphs are sometimes generalized so that nodes do not only represent users but also content or other kinds of entities. In this thesis we do not follow this approach, and model social graphs in the more traditional way.

Social graphs have some specific characteristics that distinguish them from other graphs. One of the most outstanding one is the distribution of degrees in a power law [29] such that the probability that a node has degree k is proportional to k−αfor some α > 1; α is called the power law exponent. Therefore, social graphs have a few nodes with very high degree and a lot of nodes with small degrees. OSNs tend to exhibit specific behaviors when studying some of the measures that we have explained for graphs. For instance, social networks are known to exhibit high clustering coefficients, much higher than those found in random graphs. High

Chapter2. Preliminary concepts 17

clustering is easily understood when speaking about social connections. Take as an example two adjacent nodes v and u (hence users v and u are, for instance, friends), and a third node y which is also adjacent to v. It is more likely that y will also be a friend of u than another randomly selected node of the graph. Social graphs are also small-world networks [29]. In a small-world network almost any node can be reached from every other node by a small number of hops. Mo- rover, such networks present a community structure, with nodes highly connected within the same community and poorly connected between different communities. Centrality metrics applied to social graphs allow us to study the power of every node in the network. For instance, nodes with high degree have many ties so they are considered to have more alternatives to satisfy their needs. High degree may also be an indicator of popularity. When dealing with directed graphs, it is possible to distinguish between popularity (observed by the number of incoming edges) and sociability (noted by the number of outgoing edges).

On the other hand, nodes with high closeness are more central to the extent that they can avoid the control potential of others nodes [30]. In contrast, nodes with low closeness values have to relay messages through others.

Finally, nodes with high betweenness centrality values are strategically located on the communication paths between other nodes [31,32]. This gives them the power to influence others by distorting or withholding information that passes through them. For this reason, it is said that nodes with high betweenness centrality have the responsibility to maintain the communication [33] and coordinate group processes [34].

2.2.2

Online social network websites

Nowadays, the number of OSNs is enormous and their diversity is very broad. In this section, far from summarizing the OSNs available on the Internet, we present a short summary of the networks whose data is used in this thesis.

Twitter is a famous microblogging service that allows users to publish messages up to 140 characters. Twitter has gained popularity as an almost real-time source of information and as a platform for organizing masses. On June 2015, Twitter

claimed to have more that 326 million monthly active users and 500 million Tweets sent per day [35].

Messages in the Twitter network are called tweets. Users can subscribe to other users’ updates so that they receive all their tweets, establishing in this way topo- logical links between users. These relationships are not bidirectional, so Alice can be following Bob’s updates while Bob may not be following Alice’s updates at all.

Twitter is used with different purposes and, because of that, different uses are given to each Twitter account. While behind some accounts there is only a single non-famous person who comments on his topics of interest, entire multinationals can be found behind other accounts. Even some of the news media companies have their own Twitter account. This diversity of users is both enriching and a challenge for anyone who deals with Twitter data, from its own engineers to advertisers or external data analysts.

In 2009, Twitter introduced a new feature in their network: Twitter lists. This feature allows users to create lists of Twitter accounts, so that it is possible to organize both followed and not-followed users. Each Twitter list has its own view that shows a stream of tweets from all the users included in that list. Moreover, once a list has been created, any other user of the network can subscribe to it. This feature considerably increases the functionality of Twitter lists by allowing people to use lists of other users to enhance their experience in the network. Flickr is an online photography sharing community. It is used by bloggers and webmasters to store images that will be embedded in web pages as well as by photographers who share and comment on creations. They claim to have more than 10 billion images in their system and 92 million registered users.

In a similar way as Twitter, Flickr relationships are directed. Alice can declare that Bob is her friend, while Bob may not say the same about Alice. Flickr shows in the user profile the list of friends of a given user.

Users may posts comments to Flickr photos and are able to favorite a photo, an action somehow similar to Facebook likes.

Chapter2. Preliminary concepts 19

Flickr’s group functionality allows users to create communities with common interests. Any user is able to create a group, which may be open to every other user in the network or restricted to certain users by invitations.

Last.fm is a music recommendation system and an Internet radio streaming service. It builds the user’s profile by analyzing his musical preferences based on the music he listens to on last.fm radio stations. Last.fm system is also capable of analyzing music that the user listens to on his own music player via some specific plugins. Last.fm network has more than 58 million users [36].

Users can send friendship requests to other lastfm users. After accepting one of such requests, two users become friends in the network. Users can see what their friends are listening to and send them recommendations.

Netlog was a Belgian OSN website targeted at young people. In 2010, they claimed to have over 94 million registered users.

Netlog allowed users to create a profile with photos and information from them- selves. The network allowed users to write posts into other users pages and contained also a private messaging system.

User friendships were bidirectional and were created through the classical request- accept method.