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An Extensive Survey on Sentiment Analysis and Opinion Mining: A Software Engineering Perspective

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Proceedings of Fourth International Conference on Computer and Communication Technologies

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 606))

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Abstract

Context—The authors have analyzed the opinion mining and sentiments related to software Engineering and what are the sentimental issues software engineers are facing in the current scenario. Objective—The authors have obtained the overall solutions to research issue and finding what are the research challenges and gaps related to sentiments and opinion. Conclusion—The authors of current paper, have analyzed the work done in various research papers on sentimental analysis related to software engineering. In software engineering process, the authors include a process where authors analyze and classify the positive, negative and neutral polarities of the opinions and reviews. This process is called sentiment analysis in software engineering. The authors give systematic and extensive survey on sentiment analysis and opinion mining.

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References

  1. Khairullah Khan B, Khan A (2010) Sentence based sentiment classification from online customer reviews. In: ACM, 2010

    Google Scholar 

  2. Maks I, Vossen P (2012) A lexicon model for deep sentiment analysis and opinion mining applications. Decis Support Syst 53(4):680–688

    Google Scholar 

  3. Strapparava C, Valitutti SA (2004) WordNet-affect: an affective extension of WordNet. In: Proceedings LREC 2004, Lisbon, Portugal, 2004

    Google Scholar 

  4. Valitutti A, Strapparava C (2010) Interfacing wordnet-affect with OCC model of emotions. In: Proceedings of EMOTION-2010, Valletta, Malta, 2010

    Google Scholar 

  5. Sinha V, Lazar A, Sharif B (2016) Analyzing developer sentiment in commit logs. In: Proceedings of MSR 2016 (13th international conference on mining software repositories). ACM, pp 520–523

    Google Scholar 

  6. Jongeling R, Sarkar P, Datta S, Serebrenik A (2017) On negative results when using sentiment analysis tools for software engineering research. Empir Softw Eng 2017:1–42

    Google Scholar 

  7. Bo Pang SV, Lee L (2002) Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of the conference on empirical methods in nat ural language processing (EMNLP), ACL, July 2002, pp 79–86

    Google Scholar 

  8. Padhy N, Panigrahi R, Satapathy SC (2019) Identifying the reusable components from component-based system: proposed metrics and model. Springer, pp 89–99

    Google Scholar 

  9. Guzman E, Az´ocar D, Li Y (2014) Sentiment analysis of commit comments in GitHub: an empirical study. In: Proceedings of MSR 2014 (11th working conference on mining software repositories). ACM, pp 352–355

    Google Scholar 

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Correspondence to S. Vikram Sindhu .

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Vikram Sindhu, S., Padhy, N., Shukur, M.G. (2023). An Extensive Survey on Sentiment Analysis and Opinion Mining: A Software Engineering Perspective. In: Reddy, K.A., Devi, B.R., George, B., Raju, K.S., Sellathurai, M. (eds) Proceedings of Fourth International Conference on Computer and Communication Technologies. Lecture Notes in Networks and Systems, vol 606. Springer, Singapore. https://doi.org/10.1007/978-981-19-8563-8_52

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