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Open Access
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Anushka Yeole, Kalyani Alisetty,
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- Student, Professor Department of Management, Sinhgad Institute of Business Administration and Research, Pune, MCA, Sinhgad Institute of Business Administration and Research, Pune Maharashtra, Maharashtra India, India
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Abstract
nA comprehensive study of sentiment analysis, a vital task in the realms of natural language processing (NLP) and artificial intelligence (AI). Sentiment analysis involves the extraction and classification of subjective information from textual data, determining whether the sentiment expressed is positive or negative. This paper investigates different approaches and methodologies used in sentiment analysis, encompassing machine learning models as well. Additionally, it discusses the challenges faced in sentiment analysis, such as handling sarcasm, irony, and context-dependent sentiment. Furthermore, the paper highlights the intersection of sentiment analysis with other NLP tasks, such as text summarization using Bag of Words (BOW) and Term Frequency-Inverse Document Frequency (TFIDF) and emphasizes the importance of understanding human language nuances for accurate sentiment interpretation. This project leverages MLflow and Prefect to manage, track, and orchestrate sentiment analysis machine learning experiments, ensuring efficient workflow automation and comprehensive performance evaluation. The integration of MLflow and Prefect not only enhances the reproducibility of experiments but also facilitates the seamless deployment of sentiment analysis models into production environments. By addressing the evolving complexities in textual data interpretation, this project aims to advance the field of sentiment analysis, contributing to more nuanced and accurate sentiment detection systems. Through an examination of recent research trends and applications, this paper underscores the significance of sentiment analysis in diverse domains ranging from social media monitoring to market research.
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Keywords: Text Summarization, Sentiment Analysis, NLP, AI, Human Language, Feature Extraction Techniques, Data Science Life Cycle.
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Software Engineering Tools & Technology Trends(josettt)]
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References
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- Hogenboom A, Bal D, Frasincar F, Bal M, De Jong F, Kaymak U. Exploiting emoticons in sentiment analysis. InProceedings of the 28th annual ACM symposium on applied computing 2013 Mar 18 (pp. 703-710).
- Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473. 2014 Sep 1.
- Radford A, Narasimhan K, Salimans T, Sutskever I. Improving language understanding by generative pre-training. 2018. Available form https://www.mikecaptain.com/resources/pdf/GPT-1.pdf
- Grljević O, Bošnjak Z. Sentiment analysis of customer data. Strategic Management-International Journal of Strategic Management and Decision Support Systems in Strategic Management. 2018 Sep 30;23(3).
- Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I. Attention is all you need. Advances in neural information processing systems. 2017;30.
- Wankhade M, Rao AC, Kulkarni C. A survey on sentiment analysis methods, applications, and challenges. Artificial Intelligence Review. 2022 Oct;55(7):5731-80.
- Rızvı M. Decoding Emotions: Harnessing the Power of Python for Sentiment Analysis in Social Media. The Eurasia Proceedings of Educational and Social Sciences. 2023 Oct 30;31:189-95.
- Prathi JK, Raparthi PK, Gopalachari MV. Real-time aspect-based sentiment analysis on consumer reviews. InData Engineering and Communication Technology: Proceedings of 3rd ICDECT-2K19 2020 (pp. 801-810). Springer Singapore.
- Shinde PP, Shah S. A review of machine learning and deep learning applications. In2018 Fourth international conference on computing communication control and automation (ICCUBEA) 2018 Aug 16 (pp. 1-6). IEEE.
- Gupta S. Sentiment Analysis: Concept, Analysis and Applications. Medium. Towards Data Science; 2018. Available from: https://towardsdatascience.com/sentiment-analysis-concept-analysis-and-applications-6c94d6f58c17
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Journal of Software Engineering Tools & Technology Trends
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| Volume | 11 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | June 4, 2024 | |
| Accepted | July 11, 2024 | |
| Published | July 22, 2024 |
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