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sis 20(27): e3

Research Article

Social Networks Mining and Analysis of Specific Groups (Political and Regional) by using API

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  • @ARTICLE{10.4108/eai.13-7-2018.163574,
        author={Farhan Khan and Saqib Saqib and Pireh Soomro and Asif Ali Laghari and Kamran Ali Memon},
        title={Social Networks Mining and Analysis of Specific Groups (Political and Regional) by using API},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={7},
        number={27},
        publisher={EAI},
        journal_a={SIS},
        year={2020},
        month={3},
        keywords={Social network, content analysis, Twitter},
        doi={10.4108/eai.13-7-2018.163574}
    }
    
  • Farhan Khan
    Saqib Saqib
    Pireh Soomro
    Asif Ali Laghari
    Kamran Ali Memon
    Year: 2020
    Social Networks Mining and Analysis of Specific Groups (Political and Regional) by using API
    SIS
    EAI
    DOI: 10.4108/eai.13-7-2018.163574
Farhan Khan1, Saqib Saqib1, Pireh Soomro1, Asif Ali Laghari1,*, Kamran Ali Memon2
  • 1: Department of Computer Science, Sindh Madressatul Islam University, Karachi, Pakistan
  • 2: School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
*Contact email: Asif.laghari@smiu.edu.pk

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.

Keywords
Social network, content analysis, Twitter
Received
2020-01-14
Accepted
2020-03-08
Published
2020-03-10
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-7-2018.163574

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.

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