Descobrir twitter mitjançant mètodes de ciències socials computacionals
- Autores: Jingyuan Yu
- Directores de la Tesis: Juan Manuel Muñoz Justicia (dir. tes.)
- Lectura: En la Universitat Autònoma de Barcelona ( España ) en 2021
- Idioma: catalán
- ISBN: 9788449099717
- Tribunal Calificador de la Tesis: Joan Pujol i Tarrés (presid.), Clara Selva Olid (secret.), María Luz Congosto Martínez (voc.)
- Programa de doctorado: Programa de Doctorado en Persona y Sociedad en el Mundo Contemporáneo por la Universidad Autónoma de Barcelona
- Materias:
- Enlaces
- Tesis en acceso abierto en: TDX
- Resumen
As Twitter has covered up people’s daily life, it has became one of the most important information exchange platforms, and quickly attracted scientists’ attention. Researchers around the world have highly focused on social science and internet studies with Twitter data as a real world sample, and numerous analytics tools and algorithms have been designed in the last decade. The present doctoral thesis consists of three researches, first, given the 14 years (until 2020) of history since the foundation of Twitter, an explosion of related scientific publications have been witnessed, but the current research landscape on this social media platform remained unknown, to fill this research gap, we did a bibliometric analysis on Twitter-related studies to analyze how the Twitter studies evolved over time, and to provide a general description of the Twitter research academic environment from a macro level. Second, since there are many analytic software tools that are currently available for Twitter research, a practical question for junior researchers is how to choose the most appropriate software for their own research project, to solve this problem, we did a software review for some of the integrated frameworks that are considered most relevant for social science research, given that junior social science researchers may face possible financial constraints, we narrowed our scope to solely focus on the free and low-cost software. Third, given the current public health crisis, we have noticed that social media are one of the most accessed information and news sources for the public. During a pandemic, how health issues and diseases are framed in the news release impacts public’s understanding of the current epidemic outbreak and their attitudes and behaviors. Hence, we decided to use Twitter as an easy-access news source to analyze the evolution of the Spanish news frames during the COVID-19 pandemic. Overall, the three researches have closely associated with the application of computational methods, including online data collection, text mining, complex network and data visualization. And this doctoral project has discovered how people study and use Twitter from three different levels: the academic level, the practical level and the empirical level.
