Trending Algorithm on Twitter through 2023

Saif Al-Deen H. Hassan, Hasan Al-Furiji, Mohammed Kareem Rashid, Zahraa Abed Hussein and Bhavna Ambudkar

Data and Metadata, 2024, vol. 3, 384

Abstract: Introduction: by doing so, Twitter's trending algorithm sets the benchmark for what online discussion and information flow look like. It must be clearly understood by the researchers and the users as to how it developed and impacted. Objective: this paper discusses the Twitter trending algorithm discussion until 2023, highlighting its aspects and ethical considerations. Method: to demonstrate trend identification, we adopted a cross-sectional approach that involved data mining of trends defined by the Twitter platform from January 2020 to October 2023, applying machine learning techniques. In total, 1,984,544 unique trends were identified in the two cities over the 1584 days of Twitter API research. Results: this research identified that there are many changes in the current trending algorithm regarding Twitter, and current real-time content and users’ participation are the major concerns. The assessed model, known as TrendDetector, predicts the trend of commercials to be 80 %, while the non-commercial trend is assessed to be 60 %. Trend selection was guided by the traffic of tweets, the number of users, and the extent of new content. Conclusions: user-generated activities, content, and spread, as well as the structure and design of the platform, are thus an intricate mix in the case of the trending algorithm on Twitter. It enhances the timely acquisition of information while being associated with preconditions of bias and manipulation. Future research must look at aspects such as the algorithm's transparency and the ethicality of the trends it selects

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:3:y:2024:i::p:384:id:1056294dm2024384

DOI: 10.56294/dm2024384

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