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Developing a System to Analyze Comments of Social Media and Identify Friends Category

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Intelligent Computing & Optimization (ICO 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 371))

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Abstract

Today users on the social platform are expressing their emotions, ideas, proposals and views. The opinion may articulate critical opinions in various ways and may include different polarities such as positive, negative or neutral and it is often a difficult challenge for people to appreciate the feeling of each opinion and the time it takes. The analysis of the feeling in each statement will resolve this issue. This paper presents a framework to analyze social media comments e.g. Facebook and identify a category of friends. First, some public profiles are selected and comments are retrieved from different posts of them. Secondly, those comments are stored as dataset and pre-processed for sentiment analysis. After that, the pre-processed data trained and tested in a sentiment analysis model developed by us. From the sentiment of data, we then identify friends. For example, a friend with a positive sentiment of comment can be considered as a good friend. The evaluation of the performance is measured. A decent accuracy is achieved by the system.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chattogram, 4349, Bangladesh

    Tasfia Hyder & Mohammad Shamsul Arefin

  2. Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh

    Rezaul Karim

Authors
  1. Tasfia Hyder
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  2. Rezaul Karim
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  3. Mohammad Shamsul Arefin
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Corresponding author

Correspondence to Mohammad Shamsul Arefin .

Editor information

Editors and Affiliations

  1. Faculty of Electrical & Electronic Engineering, MERLIN Research Centre, Ton Duc Thang University, Hồ Chí Minh City, Vietnam

    Pandian Vasant

  2. Faculty of Electrical Engineering and Computer Science, VÅ B TU Ostrava, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

  3. Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland

    Gerhard-Wilhelm Weber

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Hyder, T., Karim, R., Arefin, M.S. (2022). Developing a System to Analyze Comments of Social Media and Identify Friends Category. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing & Optimization. ICO 2021. Lecture Notes in Networks and Systems, vol 371. Springer, Cham. https://doi.org/10.1007/978-3-030-93247-3_74

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