Abstract
People have informal conversations on social media sites (Twitter, Facebook, etc) that shed light on the current issues around the world – opinions, and concerns about the learning process. Data from such environments can provide valuable information to predict the future to make effective decision making, however, the usage of such data is challenging. The complexity of such data from social media content requires the use of human understanding as well as social network analysis to make predictions. We focused on political groups around the world to discover linkages behind the Terrorism around the World to make predictions depend upon the data available. In this research paper, we focused on tweets related to the politicians and communities based on hashtags like #Syria #Weapons #Terrorist, etc. to identify the linkages of the user who are talking about these issues depending upon the HashTag we used for the content analysis of social network by using Gephi to make a prediction.
| Original language | English |
|---|---|
| Pages (from-to) | 1-10 |
| Number of pages | 10 |
| Journal | EAI Endorsed Transactions on Scalable Information Systems |
| Volume | 7 |
| Issue number | 27 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Farhan Khan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
Keywords
- Social network
- content analysis
ASJC Scopus subject areas
- Software
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications
- Information Systems and Management