Emotional Landscape of Social Media: Exploring Sentiment Patterns
- Title
- Emotional Landscape of Social Media: Exploring Sentiment Patterns
- Creator
- Jain K.; Panwar D.; Saini G.L.; Kumar S.
- Description
- Sentiment analysis, a pivotal research area, involves exploring emotions, attitudes, and evaluations prevalent in diverse public spheres. In the contemporary era, individuals extensively share their perspectives on various subjects through social media platforms. Twitter has emerged as a prominent microblogging site, facilitating users to express opinions and insights globally. However, disrespectful or unfair comments have prompted specific platforms to restrict user comments, highlighting the need to foster productive discourse on social media. This study addresses this imperative by analyzing sentiments using data from Twitter. This work employed various deep learning algorithms and methods to classify elements as negative or positive. The Sentiment140 dataset, sourced from Twitter, serves as the training data for the models to identify the most accurate classification approach. By delving into sentiment analysis on Twitter, the study contributes to a better understanding of the nuances of online expressions. It aims to enhance the overall quality of discourse in social media. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Lecture Notes in Networks and Systems, Vol-969 LNNS, pp. 469-479.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Deep learning; Negative; Neutral; Positive; Sentiment analysis; Social media; Tweets; Twitter
- Coverage
- Jain K., Manipal University Jaipur, Rajasthan, Jaipur, India; Panwar D., Manipal University Jaipur, Rajasthan, Jaipur, India; Saini G.L., Manipal University Jaipur, Rajasthan, Jaipur, India; Kumar S., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Kengeri Campus, Karnataka, Bangalore, 560074, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981972081-1
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Jain K.; Panwar D.; Saini G.L.; Kumar S., “Emotional Landscape of Social Media: Exploring Sentiment Patterns,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 26, 2025, https://archives.christuniversity.in/items/show/19398.