An article written with Dra. Sued-Palmeiro abour Covid-19 in Twitter using R programming and published on the Q2 Journal Cuadernos.Info.

At the beginning of the COVID19 pandemic, social platforms played a crucial role in the production and access to information. This study aims to identify the topics of most significant interest and their associated feelings during the onset of the pandemic on Spanish-language tuits. In addition, we analyzed the role of Twitter as a social platform involved in the public conversation, both as a means for mass self-communication and for amplifying the voice of a reduced set of high visibility actors. 231,375 tweets were collected in Spain and Latin America over two months. Then, the sample was analyzed with digital methods and techniques through computer programming in R. Frequency and sentiment indicators were measured, and terms were grouped to identify topics and determine users’ interests. The frequency of the main terms is dynamic throughout the period studied, suggesting different perceptions of the pandemic. The main topics refer to conversations around the number of cases, deaths, and infections. Sentiment analysis shows the prevalence of negative feelings. The analyzed sample corresponds to ordinary users’ messages for the great majority, but a part of it has been amplified on a large scale through retweets and bookmarks.

Most frequent words for the collected data:

Cebral-Loureda, M., & Sued-Palmeiro, G. E. (2021). Los inicios de la pandemia de COVID19 en Twitter. Análisis computacional de la conversación pública en lengua española. Cuadernos.Info , (49), 1-25.