Abstract
With the quick increment in the quantity of web clients, the Internet has an enormous measure of data produced by the clients. Many people share their views regarding a topic on social media platforms such as Facebook and Twitter and give their feedback or review about a product on e-commerce web sites such as Amazon and Flipkart which leads to a huge amount of data. The identification of subjective statements from the data is known as subjectivity detection. To automate the analysis of such data, sentiment analysis is used. The aim is to find the opinionative data and classify it according to its polarity, i.e. positive, negative or neutral feedback, known as sentiment classification and then analysing it which is known as sentiment analysis. However, before performing sentiment examination, the information is exposed to different pre-processing procedures which finally give the desired optimized output. This allows us to get to know about the public’s mood or opinion about a particular topic. This summarization helps the concerned organization or public to improve their product or service based on the feedback received.
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Sindhu, C., Sasmal, B., Gupta, R., Prathipa, J. (2021). Subjectivity Detection for Sentiment Analysis on Twitter Data. In: Hemanth, D., Vadivu, G., Sangeetha, M., Balas, V. (eds) Artificial Intelligence Techniques for Advanced Computing Applications. Lecture Notes in Networks and Systems, vol 130. Springer, Singapore. https://doi.org/10.1007/978-981-15-5329-5_43
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