The study of Online Social Networks offers growing opportunities to examine a number of aspects of the real world and to better understand how human society works at scale. One crucial research direction, constantly evolving over time, concerns the language adopted by users and its impact on online communities. To provide a contribution in this setting, in this paper, we adopt a multi-relational model for social network and identify a new typology of relation, namely co-interest, as an explicit common declaration of engagement towards a given topic among pair of users. Thematic communities can be, hence, derived leveraging such relations. After that, exploiting Natural Language Processing and Machine Learning techniques, we identify and define suitable analysis metrics focusing on the characteristics of the language adopted in such communities. With the objective of analyzing how the adoption of different language may impact the formation of cohesive and strong communities, to make our study general, we consider two very popular and intrinsically different social platforms, namely Twitter and Reddit. The analysis carried out in this paper aims at comparing the two social media to find interesting and novel results about how their users compose textual comments and the corresponding impact on users’ interaction. Interestingly, the obtained results show that, although the main factor is related to the popularity of the user generating the content, the characteristics of the adopted language play a non negligible role in the formation of strong communities in social systems.
The importance of the language for the evolution of online communities: An analysis based on Twitter and Reddit / M. Arazzi, S. Nicolazzo, A. Nocera, M. Zippo. - In: EXPERT SYSTEMS WITH APPLICATIONS. - ISSN 0957-4174. - 222:(2023 Jul 15), pp. 119847.1-119847.23. [10.1016/j.eswa.2023.119847]
The importance of the language for the evolution of online communities: An analysis based on Twitter and Reddit
S. NicolazzoSecondo
;
2023
Abstract
The study of Online Social Networks offers growing opportunities to examine a number of aspects of the real world and to better understand how human society works at scale. One crucial research direction, constantly evolving over time, concerns the language adopted by users and its impact on online communities. To provide a contribution in this setting, in this paper, we adopt a multi-relational model for social network and identify a new typology of relation, namely co-interest, as an explicit common declaration of engagement towards a given topic among pair of users. Thematic communities can be, hence, derived leveraging such relations. After that, exploiting Natural Language Processing and Machine Learning techniques, we identify and define suitable analysis metrics focusing on the characteristics of the language adopted in such communities. With the objective of analyzing how the adoption of different language may impact the formation of cohesive and strong communities, to make our study general, we consider two very popular and intrinsically different social platforms, namely Twitter and Reddit. The analysis carried out in this paper aims at comparing the two social media to find interesting and novel results about how their users compose textual comments and the corresponding impact on users’ interaction. Interestingly, the obtained results show that, although the main factor is related to the popularity of the user generating the content, the characteristics of the adopted language play a non negligible role in the formation of strong communities in social systems.File | Dimensione | Formato | |
---|---|---|---|
1-s2.0-S0957417423003482-main.pdf
embargo fino al 15/07/2025
Tipologia:
Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione
1.32 MB
Formato
Adobe PDF
|
1.32 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
1-s2.0-S0957417423003482-main.pdf
accesso riservato
Tipologia:
Publisher's version/PDF
Dimensione
1.32 MB
Formato
Adobe PDF
|
1.32 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.