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Sentiment Analysis Combination in Terrorist Detection on Twitter: A Brief Survey of Approaches and Techniques

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Research in Intelligent and Computing in Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1254))

Abstract

Terrorism is a big concern for many governments and people, especially with using social media such as Twitter that uses new technologies. Terrorism uses many techniques to carry out their actions and plans. Technology can play an important role in providing accurate predictions of terrorist activities. Here, we tried to do so using sentiment analysis for terrorist-related of Twitter because the early detection of terrorist activity is very important to the recent attack and to combat the spread of global terrorist activity. This work studied the techniques of effective analysis of terrorist activity data on Twitter. It is based on 17 articles that used Twitter to study terrorism for different purposes, while highlighting the different techniques used, from this survey one can notice that the machine learning techniques were used the most for sentimental analysis with good accuracy depending on the data used such as AdaBoost, support vector machine, maximum entropy, Naive Bayes, decision tree algorithms. Few number of papers are analyzed tweets in Arabic language as compared to English version because of its complexity parsing beside the complexity in analyzing feelings in Arabic makes tasks more challenging.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Mathematics, Department of Computer Science, University of Kufa, Najaf, Iraq

    Esraa Najjar & Salam Al-augby

Authors
  1. Esraa Najjar
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  2. Salam Al-augby
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Corresponding author

Correspondence to Esraa Najjar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, GIET University, Gunupur, Odisha, India

    Raghvendra Kumar

  2. Institute of Engineering and Technology, Thu Dau Mot University, Binh Duong, Vietnam

    Nguyen Ho Quang

  3. CMR Institute of Technology, Hyderabad, Telangana, India

    Vijender Kumar Solanki

  4. Universidad Don Bosco, Antiguo Cuscatlán, El Salvador

    Manuel Cardona

  5. KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

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Najjar, E., Al-augby, S. (2021). Sentiment Analysis Combination in Terrorist Detection on Twitter: A Brief Survey of Approaches and Techniques. In: Kumar, R., Quang, N.H., Kumar Solanki, V., Cardona, M., Pattnaik, P.K. (eds) Research in Intelligent and Computing in Engineering. Advances in Intelligent Systems and Computing, vol 1254. Springer, Singapore. https://doi.org/10.1007/978-981-15-7527-3_23

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