Publicação
Extraction and Exploration of Morality on Social Networks: Analyzing Twitter discussions with the Moral Foundations Theory
| Resumo: | In the last decade, social media platforms, particularly Twitter, have played a major role in shaping public discourse and influencing real-world events, ranging from political debates to social movements. The insights of the data generated on these platforms provides a unique lens through which we can analyze and understand society’s trends, making it crucial to process this information effectively. Twitter has not only enhanced people’s voices, thoughts, and sentiments but has also facilitated public discussions and information dissemination through features like tweeting, replying, and retweeting. This research aims to leverage social media data, specifically Twitter data, to uncover the underlying morality embedded in these discussions. The Moral Foundations Theory serves as an explanatory factor for variations in moral behavior, shedding light on how individuals express opinions and categorize thoughts using both individualizing and binding foundations. Understanding the interplay between morality, viral topics and user groups is of extreme importance, especially in explaining political ideologies and cross-cultural differences in moral behavior. By employing advanced natural language processing for extracting moral insights from Tweets related to viral topics, this study seeks to unravel the intricate dynamics that shape topics' lifetimes and uncover the role of morality in justifying various perspectives. The investigation draws on data obtained from the Twitter Search API, specifically focusing on the year 2020, a year in which humanity faced many challenges. Anticipated outcomes of this study include the development of a robust approach/methodology capable of providing insights and predictions on diverse challenges, such as discerning the presence of morality in specific topics. This research contributes to the evolving landscape of social science studies by addressing ambiguous questions arising from the intersection of social media, morality, and topic virality. |
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| Autores principais: | Custódio, Naomi Ferreras |
| Assunto: | Moral Foundations Theory Twitter Morality Social Media Political Annotation Topic SDG 16 - Peace, justice and strong institutions SDG 17 - Partnerships for the goals |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | In the last decade, social media platforms, particularly Twitter, have played a major role in shaping public discourse and influencing real-world events, ranging from political debates to social movements. The insights of the data generated on these platforms provides a unique lens through which we can analyze and understand society’s trends, making it crucial to process this information effectively. Twitter has not only enhanced people’s voices, thoughts, and sentiments but has also facilitated public discussions and information dissemination through features like tweeting, replying, and retweeting. This research aims to leverage social media data, specifically Twitter data, to uncover the underlying morality embedded in these discussions. The Moral Foundations Theory serves as an explanatory factor for variations in moral behavior, shedding light on how individuals express opinions and categorize thoughts using both individualizing and binding foundations. Understanding the interplay between morality, viral topics and user groups is of extreme importance, especially in explaining political ideologies and cross-cultural differences in moral behavior. By employing advanced natural language processing for extracting moral insights from Tweets related to viral topics, this study seeks to unravel the intricate dynamics that shape topics' lifetimes and uncover the role of morality in justifying various perspectives. The investigation draws on data obtained from the Twitter Search API, specifically focusing on the year 2020, a year in which humanity faced many challenges. Anticipated outcomes of this study include the development of a robust approach/methodology capable of providing insights and predictions on diverse challenges, such as discerning the presence of morality in specific topics. This research contributes to the evolving landscape of social science studies by addressing ambiguous questions arising from the intersection of social media, morality, and topic virality. |
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