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Sentiment classification within online social media using whale optimization algorithm and social impact theory based optimization

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  • Akyol, Sinem
  • Alatas, Bilal

Abstract

In recent years, social networks have become an important part of daily life and are becoming increasingly important. In this study, sentiment analysis or opinion mining, which is one of the most well-known social network analysis problems, is considered as an optimization problem for the first time. In the same way, for the first time, sentiment analysis is considered as a multi-objective problem. Whale Optimization Algorithm and Social Impact Theory based Optimization Algorithm, which are the current intelligent optimization algorithms, are adapted for the sentiment analysis problem. Furthermore, memory feature is integrated into Social Impact Theory based Optimization Algorithm in order to obtain effective results in this study. The obtained results from the proposed algorithms are also compared with thirty-three supervised learning algorithms within real IMDB, Polarity, and Amazon data sets. In order to evaluate the performance of the results; accuracy percentage, precision, recall, F-Measure, and MCC that are the five most commonly used measure in the literature are used. When the results are examined, it is observed that adapted metaheuristic optimization algorithms give more successful results in sentiment analysis problem.

Suggested Citation

  • Akyol, Sinem & Alatas, Bilal, 2020. "Sentiment classification within online social media using whale optimization algorithm and social impact theory based optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    • Handle: RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119317431
    DOI: 10.1016/j.physa.2019.123094
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    References listed on IDEAS

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    1. Shi, Yong & Tang, Ye-ran & Long, Wen, 2019. "Sentiment contagion analysis of interacting investors: Evidence from China’s stock forum," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 246-259.
    2. Joakim Westerlund, 2018. "CCE in panels with general unknown factors," Econometrics Journal, Royal Economic Society, vol. 21(3), pages 264-276, October.
    3. Wiesen, Thomas F.P. & Beaumont, Paul M. & Norrbin, Stefan C. & Srivastava, Anuj, 2018. "Are generalized spillover indices overstating connectedness?," Economics Letters, Elsevier, vol. 173(C), pages 131-134.
    4. Zhu, Hengmin & Kong, Yuehan & Wei, Jing & Ma, Jing, 2018. "Effect of users’ opinion evolution on information diffusion in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2034-2045.
    5. Chandra Sekhara Rao, S. & Manisha,, 2018. "Numerical solution of generalized Black–Scholes model," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 401-421.
    6. Oliva, Diego & Abd El Aziz, Mohamed & Ella Hassanien, Aboul, 2017. "Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm," Applied Energy, Elsevier, vol. 200(C), pages 141-154.
    7. Hu, Jian & Bansal, Manish & Mehrotra, Sanjay, 2018. "Robust decision making using a general utility set," European Journal of Operational Research, Elsevier, vol. 269(2), pages 699-714.
    8. Araújo, Tanya & Eleutério, Samuel & Louçã, Francisco, 2018. "Do sentiments influence market dynamics? A reconstruction of the Brazilian stock market and its mood," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1139-1149.
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