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- Title
Tweets Classification and Sentiment Analysis for Personalized Tweets Recommendation.
- Authors
Khattak, Asad Masood; Batool, Rabia; Satti, Fahad Ahmed; Hussain, Jamil; Khan, Wajahat Ali; Khan, Adil Mehmood; Hayat, Bashir
- Abstract
Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. After precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user's post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately.
- Subjects
MICROBLOGS; SENTIMENT analysis; CLASSIFICATION; SOCIAL networks
- Publication
Complexity, 2020, p1
- ISSN
1076-2787
- Publication type
Article
- DOI
10.1155/2020/8892552