A Situational Analytic Method for User Behavior Pattern in Multimedia Social Networks

Zhang, Zhiyong; Sun, Ranran; Wang, Xiaoxue; Zhao, Chunjiang

doi:10.1109/tbdata.2017.2657623

Cited by 31 publications

(26 citation statements)

References 23 publications

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“…Among existing social platforms, clear market leaders are Facebook followed by Twitter, hosting 2 billion and 640 million respective users, including 1.33 1.32 billion and 328 271 million active monthly users [2]- [4]. Accordingly, through user activities, i.e., interactions of the users with the OSN, terabytes of data are generated every second [5]- [7]. This vast and rich collection of user-generated content includes people's opinions about events and products; personal ideas, feelings, and interests; opinions about current societal debates and governmental policies; and much more [8].…”

Section: Introductionmentioning

confidence: 99%

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Credibility in Online Social Networks: A Survey

et al. 2019

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The importance of information credibility in society cannot be underestimated given that it is at the heart of all decision-making. Generally, more information is better; however, knowing the value of this information is essential for the decision-making processes. Information credibility defines a measure of the fitness of the information for consumption. It can also be defined in terms of reliability, which denotes the probability that a data source will appear credible to the users. A challenge in this topic is that there is a great deal of literature that has developed different credibility dimensions. In addition, information science dealing with online social networks has grown in complexity, attracting interest from researchers in information science, psychology, human-computer interaction, communication studies, and management studies, all of whom have studied the topic from different perspectives. This work will attempt to provide an overall review of the credibility assessment literature over the period 2006-2017 as applied to the context of the microblogging platform, Twitter. The known interpretations of credibility will be examined, particularly as they relate to the Twitter environment. In addition, we investigate levels of credibility assessment features. We then discuss recent works, addressing a new taxonomy of credibility analysis and assessment techniques. At last, a cross-referencing of literature is performed while suggesting new topics for future studies of credibility assessment in a social media context.

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Section: Introductionmentioning

confidence: 99%

“…Access to such data may be very interesting to a wide range of organizations [3], since patterns of action can be deducted based on the input originating on social networks [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Credibility in Online Social Networks: A Survey

et al. 2019

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“…Such an analysis is useful to understand the dynamic needs of a software service environment. Zhang et al [13] presented a framework to the discovery of user behavior pattern in multimedia video recommendation services on online social networks. Their framework is based on social context and analyzes the changes in user need for different social situations.…”

Section: Related Work a Behavior Analysismentioning

confidence: 99%

Detecting Malicious Social Bots Based on Clickstream Sequences

2019

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“…The present practice initially relies on guidelines and policies to deprive the types of publishable data and on agreements on the use and storage of sensitive data. The limitation of this approach is that it either manipulates data overly or requires a trust level that is practically very low in many present data sharing scenarios [4,5]. For instance, contracts and agreements between any parties cannot ensure that sensitive data will not be carelessly misplaced and end up in the wrong hands.…”

Section: Introductionmentioning

confidence: 99%