The analysis of people’s comments in social platforms is a widely investigated topic because comments are the place where people show their spontaneity most clearly. In this article, we present a network-based data structure and a related approach to represent and manage the underlying semantics of a set of comments. Our approach is based on the extraction of text patterns that take into account not only the frequency, but also the utility of the analysed comments. Our data structure and approach are ‘multidimensional’ and ‘holistic’, in the sense that they can simultaneously handle content semantics from multiple perspectives. They are also easily extensible, because additional content semantics perspectives can be easily added to them. Furthermore, our approach is able to evaluate the semantic similarity of two sets of comments. In this article, we also illustrate the results of several tests we conducted on Reddit comments, even if our approach can be applied to any social platform. Finally, we provide an overview of some possible applications of this research.

Representation, detection and usage of the content semantics of comments in a social platform / Bonifazi, G.; Cauteruccio, F.; Corradini, E.; Marchetti, M.; Terracina, G.; Ursino, D.; Virgili, L.. - In: JOURNAL OF INFORMATION SCIENCE. - ISSN 1741-6485. - 50:2(2024), pp. 317-341. [10.1177/01655515221087663]

Representation, detection and usage of the content semantics of comments in a social platform

G. Bonifazi
;
F. Cauteruccio
;
E. Corradini
;
M. Marchetti
;
D. Ursino
;
L. Virgili
2024-01-01

Abstract

The analysis of people’s comments in social platforms is a widely investigated topic because comments are the place where people show their spontaneity most clearly. In this article, we present a network-based data structure and a related approach to represent and manage the underlying semantics of a set of comments. Our approach is based on the extraction of text patterns that take into account not only the frequency, but also the utility of the analysed comments. Our data structure and approach are ‘multidimensional’ and ‘holistic’, in the sense that they can simultaneously handle content semantics from multiple perspectives. They are also easily extensible, because additional content semantics perspectives can be easily added to them. Furthermore, our approach is able to evaluate the semantic similarity of two sets of comments. In this article, we also illustrate the results of several tests we conducted on Reddit comments, even if our approach can be applied to any social platform. Finally, we provide an overview of some possible applications of this research.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/296426
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