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Patterns of human and bots behaviour on Twitter conversations about sustainability
Mary Luz Mouronte-López1, Javier Gómez Sánchez-Seco2,3, Rosa M Benito3
1Higher Polytechnic School, Universidad Francisco de Vitoria, Carretera Pozuelo a, Av de Majadahonda, Km 1.800, 28223, Madrid, Spain. maryluz.mouronte@ufv.es.
Scientific Reports
|February 8, 2024
Summary
This study analyzed sustainability discussions on Twitter, differentiating between human and bot accounts. Findings reveal positive sentiment in most messages, with bots posting more neutral content and distinct keyword usage patterns.
Area of Science:
- Social Sciences
- Computer Science
- Environmental Science
Background:
- Sustainability is a critical global issue.
- Twitter is a major social network for public discourse.
- Understanding online sustainability conversations is vital.
Purpose of the Study:
- To analyze sustainability-related activity on Twitter.
- To model and differentiate between human and bot accounts.
- To investigate user behavior and sentiment in sustainability discussions.
Main Methods:
- Developed a mathematical model to classify Twitter accounts (bot vs. human).
- Employed clustering analysis to identify posting and retweeting patterns.
- Conducted lexicon-based sentiment analysis (2006-2022) and keyword centrality analysis.
Main Results:
- Identified distinct behavioral patterns between human and bot users.
- Found predominantly positive sentiment in messages from both account types.
- Bots exhibited a higher proportion of neutral messages compared to humans.
- Observed commonalities and differences in keyword usage between humans and bots.
Conclusions:
- Twitter serves as a significant platform for sustainability discourse.
- Bots and human users exhibit unique characteristics in their online sustainability engagement.
- Sentiment analysis and behavioral patterns offer insights into online social issues.
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