Profiling Bots and Fake News Spreaders at PAN'19 and PAN'20 : Bots and Gender Profiling 2019, Profiling Fake News Spreaders on Twitter 2020

This paper synthesizes our participation in the CLEF conference 2020 regarding the Profiling Fake News Spreaders on Twitter task, organized at the PAN lab on digital text forensics and stylometry. Our team obtained one of the two best performing results with an average accuracy of 0.7775 -0.7350 for...

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Bibliographic Details
Published in2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA) pp. 626 - 630
Main Author Pizarro, Juan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2020
Subjects
Author Profiling
Birds
Blogs
Bot identification
Fake News
Gender Identification
Social networking (online)
Support vector machines
Task analysis
Training
Tuning
Twitter
Online AccessGet full text
DOI10.1109/DSAA49011.2020.00088

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Summary:This paper synthesizes our participation in the CLEF conference 2020 regarding the Profiling Fake News Spreaders on Twitter task, organized at the PAN lab on digital text forensics and stylometry. Our team obtained one of the two best performing results with an average accuracy of 0.7775 -0.7350 for English and 0.8200 for Spanish. In summary, we submit a Support Vector Machine (SVM) classifier trained with character and word n-gram to determine whether the author of a tweet feed is keen to be a spreader of fake news. Besides, we present our results as the best performing team in Bots and Gender Profiling 2019 with an average accuracy of 0.8805. Its goal was to determine if the author of a tweet feed was a bot or human, followed by identifying her/his gender in the case of humans.
DOI:10.1109/DSAA49011.2020.00088