Collective Behavior of social Networking Sites

Vispute, Ashwini; Jadhav, Prerna; Kharat, Priyanka

doi:10.9790/0661-16227579

Cited by 2 publications

(1 citation statement)

References 12 publications

(11 reference statements)

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“…According to Zafarani et al [35], Zafarani and Huan [34], Vispute et al [30] user behavior on social networking sites is how users act and interact with events and phenomena on social networks. User behavior includes actions performed by users on social networking sites such as sharing entry, posting entry, liking posts, commenting on posts, bookmarking, following, creating and joining groups and communities, etc.…”

Section: User Behaviors In the Social Networkmentioning

confidence: 99%

A Method to Classify Users on Social Networks Based on Similarity Mesuring

Nguyen

2024

ijmst

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With the express growth of social networks, users have joined more and more of these networks and live their lives virtually. Consequently, they create huge amounts of data on these social networks: their profile, interests, and behaviors such as posting, commenting, liking, joining groups or communities, etc. One of the basic issues in these challenges is the problem of estimating the similarity among users on these social networks based on their profile, interests, and behavior. This paper presents a model for estimating the similarity between users based ontheir behavior on social networks. The considered behaviors are activities including posting or sharing entries, liking these entries, commenting and liking the comments in these entries, and joining a group in the social networks. The model is then evaluated with a dataset collected from Facebook users. The results show that the model correctly estimates the similarity among users in the majority of cases.

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Section: User Behaviors In the Social Networkmentioning

confidence: 99%