What is it about?
The anonymity (total or partial) allowed in various social networks and messaging applications brought a sense of impunity to many users. The ease of publishing or sharing content, including fake news and defamatory comments, has been a major challenge to democratic debate on social networks. The attribution of authorship aims to identify the authors of comments, both to give due value to the authors of a given text, but also to correctly identify those responsible for inappropriate comments. In this work, different approaches were implemented for the attribution of authorship, reaching accuracy rates above 97%.
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Why is it important?
The research on authorship attribution began decades ago. A relevant characteristic of the present work is to consider the temporal information of the posts, assuming that an author's writing style can undergo gradual changes over the months. The results reveal that the attribution of authorship considering the temporal information presented results equal or superior to the state-of-the-art for this problem.
Perspectives
This work showed the relevance of using temporal information in the training of classification algorithms for the author attribution problem. The pertinence of attribution of authorship today is greater than at any time in the past of humanity. In addition to the challenges of using temporal information in posts on social networks, new opportunities arise for analysing the context of the social network in which the user finds himself.
Dr. Luciano Antonio Digiampietri
Universidade de Sao Paulo Campus da Capital
Read the Original
This page is a summary of: Authorship Attribution with Temporal Data in Reddit, May 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3535511.3535515.
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