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This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract The nature of free information diffusion and sharing in social networks SNs has increasingly attracted users to gather in communities to facilitate communication, resulting in increased challenges to community influence analysis in SNs.
In SNs, the ability to evaluate how a community affects other users and communities is essential for further applications. Although considerable effort has been expended on the influence evaluation of individuals, little attention has been paid to influence evaluation of the community as a whole—particularly when considering the inherent features of dynamic changes of influence over time.
This paper proposes a community related influence evaluation model with a dynamic perspective D-CIEM that reflects two types of influence, entity influence and community-initiated influence, by considering dynamic effects over time.
Our work includes the following main points: We present community-initiated dynamic influence evaluation methods, including methods to calculate community influence for internal and external users and for other communities.
Finally, we provide evaluation results to verify the performance of our model. Introduction Social networks have garnered increasing attention for both personal communications and business transactions [ 12 ]. A social network SN is composed of numerous individual users who join the social network and impact each other to various degrees through the platform [ 3 ].
As an organization with massive numbers of members, a community naturally has a wider impact on users than does a single individual in an SN [ 4 ]. Therefore, it is important to analyze the potential influence of the SN community as an entity. However, communities in SNs have characteristics such as dynamic member organization and complex inner relationships between members that create challenges to analysis.
The problem of influence evaluation is of wide concern [ 24 — 8 ]. By measuring the properties of an entity in a social network, it is possible to determine how much influence that entity has and how it impacts the social network; therefore, influence analysis is an important facet of social network analysis [ 8 ].
However, little attention has been paid to mining another significant entity in SNs, i. Which perspectives are considered is critical for community influence analysis. Essentially, the influences of communities on users are the results of user interactions: Some efforts have recently been made to evaluate influence in social networks [ 11 ].
There are two kinds of influence evaluation methods in social networks: Communities have more impact in social networks than do single individuals because a community is a well-organized group, and everyone in the community contributes his or her impact to the whole.
Group-organized influence evaluation often identifies users who play significant roles in group work rather than individuals who have great influence. For example, based on a specific topic, by analyzing community influence after community identification, we can find the community that has the greatest effect in spreading the topic and significantly affects further topic diffusion or public opinion supervision.
However, the complexity of the inner relationships of a community results in difficulties when evaluating community influence. Because other factors such as the passage of time and dynamic changes in community composition may introduce changes to the community, the influence of the community may also change.
Thus, it is essential to accurately represent the influence of a community dynamically. In this work, we propose a new scheme for evaluating community related influence from a dynamic perspective. We consider that there are two kinds of community related influence: More specially, we consider that community influence indicates a comprehensive impact formed by all of its members, while the community-initiated influence indicates the impacts from the community to other entities in social network.
Therefore, we propose a dynamic community related influence evaluation model D-CIEM that includes three types of influence evaluation: The main works of this paper are as follows.
We verify the feasibility and effectiveness of the proposed method by experimental results. We aim to achieve the following contributions. That is, most traditional models calculate the influence of entities in social network including individual user or community without time dimension.
In our paper, we consider the community as a dynamical entity and therefore the influence of community is calculated from three aspects: Therefore, the influence of community is calculated based on the two different structure features.Change the relative evaluation of attributes.
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