File Name: detecting opinion leaders and trends in online social networks .zip
Opinion leadership is leadership by an active media user who interprets the meaning of media messages or content for lower-end media users. Typically the opinion leader is held in high esteem by those who accept their opinions. Opinion leadership comes from the theory of two-step flow of communication propounded by Paul Lazarsfeld and Elihu Katz. Merton , C. Wright Mills and Bernard Berelson.
Kempe, J. Tardos, Maximizing the spread of influence through a social network. In Proceedings of the ninth acm sigkdd international conference on knowledge discovery and data mining, , pp. Zhao, S. Li and F. Jin, Identification of influential nodes in social net- works with community structure based on label propagation. Neurocomputing, , , pp.
It is valuable for the real world to find the opinion leaders. Because different data sources usually have different characteristics, there does not exist a standard algorithm to find and detect the opinion leaders in different data sources. Every data source has its own structural characteristics, and also has its own detection algorithm to find the opinion leaders. Experimental results show the opinion leaders and theirs characteristics can be found among the comments from the Weibo social network of China, which is like Facebook or Twitter in USA. With further study, the definition of opinion leader expands.
Forum has long been the main way of communication, and more and more users publish their opinions by it. The most influential users or opinion leaders will contribute to the formation of information, especially the positive influential users who can guide public opinions and make positive influence. Positive Opinion Leader Group POLG represents a group of users, each of who expresses the similar content and same sentiment orientation with their followers to a great extent, who are regarded as the most influential men during the information dissemination process. However, most existing researches pay less attention to the implicit relationship, heterogeneous structure and positive influence. In this paper, we focus on modeling multi-themes user network of forum with explicit and implicit links for this purpose. In detail, we put forward a data structure L ongest S equence P hrase Tree LSP-Tree for representing comments on forum, measuring the similarity between comments based on LSP-Tree to obtain implicit links, and further detecting positive opinion leader group.
Social media has reshaped individual and institutional communication. The unrestricted access to spontaneous views and opinions of society can enrich the evaluation of healthcare interventions. Antimicrobial resistance has been identified as a global threat to health requiring collaboration between clinicians and healthcare users. We sought to explore events and individuals influencing the discourse about antibiotics on Twitter. A web-based tool www. Activity peaks message frequency over three times that of baseline were analysed to identify events leading to the increase.
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The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics. A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event.
Стратмор бесшумно спускался по ступенькам. Незачем настораживать Хейла, давать ему знать, что они идут. Почти уже спустившись, Стратмор остановился, нащупывая последнюю ступеньку. Когда он ее нашел, каблук его ботинка громко ударился о кафельную плитку пола.
Ну вот, на Мидж снова что-то нашло.
А это не так? - язвительно заметил Хейл. Сьюзан холодно на него посмотрела. - Да будет. - Хейл вроде бы затрубил отбой. - Теперь это не имеет значения. У вас есть ТРАНСТЕКСТ.
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