Sentiment analysis using Twitter data
A Comparative Application of Lexicon- And Machine-Learning-Based Approach
Bibliographic Data
| ID | 4614696 |
|---|---|
| Authors | Yuxing Qi, Yu‐Xing Qi (King's College London), Zahratu Shabrina (0000-0001-8246-8229, King's College London, corresponding author) |
| Year | 2023 |
| Volume | 13 |
| Issue | 1 |
| Pages | 31-31 |
| Publication date | 2023-02-09 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-023-01030-x |
| PMID | 36789379 |
| OpenAlex | W4319984444 |
| Language | EN |
| Citations received | 19 |
| References cited | 30 |
Social media platform such as Twitter provides a space where users share their thoughts and opinion as well as connect, communicate, and contribute to certain topics using short, 140 characters posts, known as tweets . This can be done through texts, pictures, and videos, etc., and users can interact using likes, comments, and reposts buttons. According to Twitter ( https://investor.twitterinc.com ), the platform has more than 206 million daily active users in 2022, which is defined as the number of logged accounts that can be identified by the platform and where ads can be shown. As more people contribute to social media, the analysis of information available online can be used to reflect on the changes in people's perceptions, behavior, and psychology (Alamoodi et al. 2021 ). Hence, using Twitter data for sentiment analysis has become a popular trend. The growing interest in social media analysis has brought more attention to Natural Languages Processing (NLP) and Artificial Intelligence (AI) technologies related to text analysis
Data science · Lexicon · Machine learning · Natural language processing · Sentiment analysis · Advanced Text Analysis Techniques · Computer Science · Sentiment Analysis and Opinion Mining · Spam and Phishing Detection · Artificial Intelligence
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| Unique citing works | 19 |
|---|---|
| Citations per year | 6,33 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 18 |