THE IMPORTANCE OF ACTORS IN THE FLOW OF INFORMATION FROM A SOCIAL NETWORK
Social networks express the world in movement, as social networks refer to a group of people (or organizations or other social entities) connected by social relationships, motivated by friendship and by work relationships or sharing of information and, through these connections, they build and rebuild the social structure.
The network must be studied by sharing information, aiming to distinguish the position and connections that actors maintain in its structure, allowing us to identify their influence on this network.
In the network environment, the sharing of information and knowledge between people is constant, as people often like to share what they know.
The willingness to share and the efficient sharing of information among the actors in a network ensure gains, because each participant improves, making use of the information to which they have access and which can reduce uncertainties and promote mutual growth.
Thus, two premises in sharing the flow of information on the network are fundamental, the centrality and strong and weak links.
In the network we will analyze, we will identify the centrality, which actors occupy the most central positions in the network, distinguishing their functions and importance in the network. This is important because it allows us to know which actors have more strength but the ability to replicate content, which content is more or less relevant. And what about the strong and weak bonds we will emphasize the distinctions of these connections, portraying the egocentric networks of some of the most influential actors. To achieve this aim, we will adopt the methodology Social Network Analysis (ARS) which studies patterns of relationships between people, organizations, states, posts, interactions, etc. and maps relationship networks based on the flow of information.
A ARS It is considered an important instrument for studying relationships that encourage the sharing of information and knowledge. It is a tool that allows the identification of indicators of relationship patterns that improve cooperation. In short, it is a resource that supports organizational management, identifying the most influential actors in the network.
In the image below (Image 01 – complete network) The network below is made up of 50 posts from 42 thousand users, from a specific network set in the period of June and July 2017, which will be kept anonymous to protect users. The image on the side, (Image 01.1 – Posts and Relationship between them – Pink: Posts. Yellow: Relationship between Posts), demonstrates the 50 posts and their relationships.
Image 01 – Complete Network
Image 01.1 – Posts and Relationship between them – Pink: Posts. Yellow: Relationship between Posts
CENTRALITY OF NETWORK ACTORS
Centrality, is a sociological resource in which an individual is central in a network when he can communicate directly with many others, or is close to many actors, or even when there are many actors who use him as an intermediary in their communications.
Actors who have more connections than other actors may be in a more advantageous position. Because they have many connections, they have alternative ways to satisfy needs and take advantage of network resources and, thus, have less dependence on other actors. In this case study, we will present the rates of centrality of network actors, highlighting its functions on the network. We applied four centrality measures in this analysis:
- Information Centrality;
- Degree Centrality;
- Betweenness Centrality;
- Closeness centrality.
In the image (Image 2 – Importance of Posts), below we can see that the larger the node, the greater the importance of the actor (at the) on the network. In this case, as we are filtering 50 posts, regarding the centrality of a node, that is, the post, the greater its importance, the greater its size in the image.
Image 02 – Importance of Posts
The image below (Image 03 – Post Interactions) it is the relationship between posts and users; all people who interacted with this post in the time period. In this image we only have the interactions, all nodes have been removed. As you can see, there are some interactions that have larger networks. The brighter the interactions, the greater amounts of activity in that interaction.
Image 03 – Post Interactions
1. Information Centrality (information centrality);
It is the centrality measure that employs the statistical approximation theory (statistical estimation). Based on the concept of information, it uses a combination that analyzes all paths between actors. For each route analyzed, the information contained in the corresponding route is considered. The most used centrality measures – degree, intermediation and proximity – on social networks they use geodesic paths (shorter) in your calculation. As the flow of information in a network can use any available channel and this is not always the shortest. To analyze this measure, we are not considering who transmits information to whom, but the existence or not of a path in which information can flow; a shorter or longer route.
We will continue next week. If you want to be notified when the article is ready, fill out the form with your email below:
[mailmunch-form id=”555544″]
