Identification of Query-Oriented Influential Users in Online Social Platform
- Resource Type
- Conference
- Authors
- Dhali, A.; Gomasta, S.S.; Mohanta, S.; Anwar, M.M.
- Source
- 2020 IEEE Region 10 Symposium (TENSYMP) Region 10 Symposium (TENSYMP), 2020 IEEE. :973-976 Jun, 2020
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Social networking (online)
Blogs
Sports
Teleportation
Data mining
Sociology
Multimedia Web sites
Influential User
TwitterRank
Multiple Specific Topics
Tracking Over Time
- Language
- ISSN
- 2642-6102
In recent time, online social influencers are affecting perceptions and behaviors of their connections by becoming a medium of swaying opinions. As a result, influential user identification has become inevitable to analyze the dynamic evolution of Online Social Networks (OSNs) for any new strategy either for viral marketing applications or controlling the propagation of provoking information. Our objective is to detect the influential users on Twitter, an online social networking with a flow of remarkable interconnections. Our proposed method is to demonstrate influential users using a collection of tweets matching a specified query on multiple topics in different time period by applying temporal TwitterRank. We conduct this experiments on real dataset to denote the effectiveness and performance of the proposed method. The findings provide that an user can achieve great influence based on number of tweets in various time period and the number of followers. This result also suggests that one topological measure alone may reflect less about the influence of users and provide new insights for sociology and other concepts. According to the proposed method, the experimental result shows the dynamic rank of influential users across multiple topics and time.