ItemConference Paper

Unveiling Sentiment Trends: An Approach to Utilize Machine Learning in Studying User Activities on New Social Applications

Title
Unveiling Sentiment Trends: An Approach to Utilize Machine Learning in Studying User Activities on New Social Applications
Creator
Chinmayi, P.; Jeswani, Himanshi; Singh, Nandini; Vinay, M.; Jayapriya, J.; Jayadurga, R.
Description
Sentiment analysis is the examination of textual data to determine the writer's attitude, which can be positive, negative, or neutral. In the context of social media analysis, sentiment analysis is peculiar as it helps to identify trends in large amounts of data that are posted by social media users. In the case of sentiment analysis algorithms, the text is categorized into positive, negative, and neutral. Classification of sentiments involves the use of several algorithms such as the decision tree, support vectors, and neural networks. In other words, the paper intends to determine the users sentiment using the decision tree model. Some of the common data sets that have been utilized in this study include the COVID-19 pandemic data, movie reviews, and product ratings. What is tried to be accomplished in this type of case is to determine the efficiency and stability of the decision trees, as well as their optimum success region. Based on the results, it can be pointed out that the accuracy is the highest for the COVID-19 Tweets dataset when referring to the simulation model, which is 98%; hence, the decision tree is best used in the context of the health sector. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Source
Lecture Notes in Networks and Systems;Volume;1377 LNNS;pp.259-269
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Accuracy; Decision trees; Machine learning techniques; Sentimental analysis
Coverage
Chinmayi P., Christ University, Karnataka, Bangalore, India; Jeswani H., Christ University, Karnataka, Bangalore, India; Singh N., Christ University, Karnataka, Bangalore, India; Vinay M., Christ University, Karnataka, Bangalore, India; Jayapriya J., Christ University, Karnataka, Bangalore, India; Jayadurga R., Christ University, Karnataka, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 23673370; ISBN: 978-981965369-0;
Format
online
Language
English
Type
Conference paper

Citation

Chinmayi, P.; Jeswani, Himanshi; Singh, Nandini; Vinay, M.; Jayapriya, J.; Jayadurga, R., “Unveiling Sentiment Trends: An Approach to Utilize Machine Learning in Studying User Activities on New Social Applications,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25564.

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