Abstract
Social media consists of interactive applications which bring together people from different geographical regions through technology. Online communities have become increasingly popular due to their capabilities to virtually connect people with similar interests. Based on their activity, a social rank is computed to measure how users are perceived within the community. The aim of this paper is to perform an in-depth analysis of a debate community from Reddit. Our method provides tailored services capable to analyze user behavior based on regularity measures, model the interactions between participants, and predict a social rank for users based on their participation. The ReaderBench framework has been used to generate multiple indices, including those for textual complexity, reflective of writing style specificities. Various regression models were trained and evaluated in order to predict users’ rankings, which are reflected in the number of votes they receive from their peers. The results show that the user ranks are predicted with a precision of 15 votes by using MLP neural networks.
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Acknowledgements
This work was funded by the Operational Programme Human Capital of the Ministry of European Funds through the Financial Agreement 51675/09.07.2019, SMIS code 125125 and by a grant of the Romanian Ministry of Research and Innovation, CCCDI—UEFISCDI, project number PN-III-P1-1.2-PCCDI-2017-0689 /”Revitalizing Libraries and Cultural Heritage through Advanced Technologies.”
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Fetoiu, CE., Dascalu, MD., Calin, M.A., Dascalu, M., Trausan-Matu, S., Militaru, G. (2021). Cohesion Network Analysis for Predicting User Ranks in Reddit Communities. In: Mealha, Ó., Rehm, M., Rebedea, T. (eds) Ludic, Co-design and Tools Supporting Smart Learning Ecosystems and Smart Education. Smart Innovation, Systems and Technologies, vol 197. Springer, Singapore. https://doi.org/10.1007/978-981-15-7383-5_15
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DOI: https://doi.org/10.1007/978-981-15-7383-5_15
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