Understanding Types of Users on Twitter
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Abstract (arXiv)
People use microblogging platforms like Twitter to involve with other users for a wide range of interests and practices. Twitter profiles run by different types of users such as humans, bots, spammers, businesses and professionals. This research work identifies six broad classes of Twitter users, and employs a supervised machine learning approach which uses a comprehensive set of features to classify users into the identified classes. For this purpose, we exploit users' profile and tweeting behavior information. We evaluate our approach by performing 10-fold cross validation using manually annotated 716 different Twitter profiles. High classification accuracy (measured using AUC, and precision, recall) reveals the significance of the proposed approach.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jun 2014.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
5 papers.
- 2021TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labelscited by 11
- 2025Agent-based simulation of online social networks and disinformationcited by 3
- 2021Seeing and Believing: Evaluating the Trustworthiness of Twitter Userscited by 2
- 2022Trust and Believe -- Should We? Evaluating the Trustworthiness of Twitter Userscited by 2
- 2026Should LLM Agents Decide in Social Simulations? Comparing Finite-State and LLM-Based Decision Policiescited by 0
- 2026Should LLM Agents Decide in Social Simulations? Comparing Finite-State and LLM-Based Decision Policies10 Jun 2026
- 2025Agent-based simulation of online social networks and disinformation26 Dec 2025
- 2022Trust and Believe -- Should We? Evaluating the Trustworthiness of Twitter Users27 Oct 2022
- 2021TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels4 Oct 2021
- 2021Seeing and Believing: Evaluating the Trustworthiness of Twitter Users16 Jul 2021