Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations
This paper advances the integration of Social Network Analysis (SNA) and topic detection into the study of Social Representations (SRs). We suggest that a combination of the two analyses helps to detect communities characterised by shared contents and/or social interactions, the two facets that make...
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Ubiquity Press
2024-12-01
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| Series: | International Review of Social Psychology |
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| Online Access: | https://account.rips-irsp.com/index.php/up-j-irsp/article/view/973 |
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| author | Valentina Rizzoli Anderson da Silveira Mirella De Falco Mauro Sarrica |
| author_facet | Valentina Rizzoli Anderson da Silveira Mirella De Falco Mauro Sarrica |
| author_sort | Valentina Rizzoli |
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| description | This paper advances the integration of Social Network Analysis (SNA) and topic detection into the study of Social Representations (SRs). We suggest that a combination of the two analyses helps to detect communities characterised by shared contents and/or social interactions, the two facets that make representations ‘social’. Building on Moliner’s (2023) proposal we present a step-by-step approach to combine the identification of shared meanings based on lexicometric analysis and identification of social interaction based on social network analysis techniques. To illustrate our proposal, we use a dataset of 396 Brazilian tweets about the Covid-19 pandemic that was collected to investigate the SR of science during the pandemic. The Reinert method was run on the corpus using the Iramuteq R interface and a bipartite network analysis was performed using Gephi software. We thus operationalised 615 users and six topics as nodes, while shared topics and interactions (883 mentions) as arcs. This allowed us to examine both the content of social representations and interactions among different individuals and communities. In our case, the results highlight shared content as the main determinant for community formation; however, some users appear to have linked different communities together: they are associated to a community not because of the topic they share, but because of their interactions with other users. We contend this methodology proves to be a fruitful theoretical-methodological link between SNA and SR theory, as it detects both facets of the relationship between SRs and groups: the shared contents and the communicative interactions between individuals. |
| format | Article |
| id | doaj-art-1b299bb4c9014bf79e3ce861b51c30ed |
| institution | Kabale University |
| issn | 2397-8570 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Ubiquity Press |
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| series | International Review of Social Psychology |
| spelling | doaj-art-1b299bb4c9014bf79e3ce861b51c30ed2025-01-08T07:57:40ZengUbiquity PressInternational Review of Social Psychology2397-85702024-12-01371212110.5334/irsp.973973Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social RepresentationsValentina Rizzoli0https://orcid.org/0000-0001-6240-4519Anderson da Silveira1https://orcid.org/0000-0002-6231-2574Mirella De Falco2https://orcid.org/0009-0002-3029-9886Mauro Sarrica3https://orcid.org/0000-0003-1167-2788Department of Communication and Social Research, Sapienza University of RomeDepartment of Psychology, Federal University of Santa CatarinaDepartment of Communication and Social Research, Sapienza University of RomeDepartment of Communication and Social Research, Sapienza University of RomeThis paper advances the integration of Social Network Analysis (SNA) and topic detection into the study of Social Representations (SRs). We suggest that a combination of the two analyses helps to detect communities characterised by shared contents and/or social interactions, the two facets that make representations ‘social’. Building on Moliner’s (2023) proposal we present a step-by-step approach to combine the identification of shared meanings based on lexicometric analysis and identification of social interaction based on social network analysis techniques. To illustrate our proposal, we use a dataset of 396 Brazilian tweets about the Covid-19 pandemic that was collected to investigate the SR of science during the pandemic. The Reinert method was run on the corpus using the Iramuteq R interface and a bipartite network analysis was performed using Gephi software. We thus operationalised 615 users and six topics as nodes, while shared topics and interactions (883 mentions) as arcs. This allowed us to examine both the content of social representations and interactions among different individuals and communities. In our case, the results highlight shared content as the main determinant for community formation; however, some users appear to have linked different communities together: they are associated to a community not because of the topic they share, but because of their interactions with other users. We contend this methodology proves to be a fruitful theoretical-methodological link between SNA and SR theory, as it detects both facets of the relationship between SRs and groups: the shared contents and the communicative interactions between individuals.https://account.rips-irsp.com/index.php/up-j-irsp/article/view/973social representationssocial network analysiscommunity detectiontopic detectionreinert methodgroups |
| spellingShingle | Valentina Rizzoli Anderson da Silveira Mirella De Falco Mauro Sarrica Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations International Review of Social Psychology social representations social network analysis community detection topic detection reinert method groups |
| title | Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations |
| title_full | Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations |
| title_fullStr | Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations |
| title_full_unstemmed | Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations |
| title_short | Two Sides of the Same Coin: How to Integrate Social Network Analysis and Topic Detection to Investigate Shared Contents and Communicative Interactions in Social Representations |
| title_sort | two sides of the same coin how to integrate social network analysis and topic detection to investigate shared contents and communicative interactions in social representations |
| topic | social representations social network analysis community detection topic detection reinert method groups |
| url | https://account.rips-irsp.com/index.php/up-j-irsp/article/view/973 |
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