Sociocultural factors during COVID-19 pandemic: Information consumption on Twitter

Abstract

The purpose of the research is to describe the sociocultural factors that emerged during the COVID-19 pandemic. Twitter is used as an instrument for data collection. The study is qualitative and uses the netnographic method. To analyze the flow of messages posted on Twitter, the model proposed by Perez-Cepeda and Arias-Bolzmann (2020) , which describes sociocultural factors, is taken as a basis. The semantics that people use are a type of functional knowledge that reveals sociocultural factors. Sentiments were analyzed through lexicon-based methods, which are the most suitable. The categorization and classification of the data are performed based on the information that users post on Twitter. The tweets related to COVID-19 describe the sociocultural issues and the level of sentiment around the pandemic. The discussion centers on the COVID-19 pandemic, information consumption, lexicon, sociocultural factors and sentiment analysis. The study was limited to the social media Twitter; another limitation was not to consider the social group of the users who interact with @pandemic_Covid-19, official account of the World Health Organization (WHO). This research contributes to the social sciences, focusing on sociocultural interaction through the use of the social network Twitter. It describes the link between sociocultural factors and the level of sentiment on issues related to the COVID-19 pandemic.

Using Social Media Data to Explore Urban Land Value and Sentiment Inequality: A Case Study of Xiamen, China

“…Social media data has a wide range of applications in various fields. Most studies have used twitter data for text analysis and recognition for evaluation and prediction studies in the fields of economy, society, market, policy, and public events [10][11][12]. Although recent studies utilized quantitative techniques, few evaluated the causes of spatial differences in sentiments from sociology and public health perspectives, and wealth-biased inequality has been ignored [13].…”

Sociocultural Factors in Times of Global Crisis

“…Regarding sociocultural factors, Perez-Cepeda and Arias-Bolzmann (2020) recommended observing how people interpret the information they consume in digital media and how the information influences sociocultural factors. For which, they propose to use the model that describes cultural factors (Pérez, 2019;Perez-Cepeda & Arias-Bolzmann, 2020;Perez-Cepeda & Arias-Bolzmann, 2021;Perez-Cepeda & Arias-Bolzmann, 2022) in order to compare sociocultural contexts that arise from studies on social domains taking as a source of information the conversations that flow on the social network Twitter.…”

“…Based on the results, it can be determined that, in the structure of the tweets, the frequent use of data composed of the combination of images, texts and objects is evidenced, which allows describing how people consume information in multiple social spaces (Arnould & Thompson, 2007). As a result, it can also be stressed that the way messages are structured allows people to consume information and interact with each other, and in this way make sense of things (Lawrence & Dover, 2015;Küçükömürler & Özkan, 2018;Perez-Cepeda & Arias-Bolzmann, 2022). RQ2: What are the issues addressed by users who interact with @gofundme?…”

Machine Learning Techniques for Sentiment Analysis of COVID-19-Related Twitter Data

“…Since the outbreak of COVID-19, social media has become pivotal in staying connected with family, friends, and colleagues, but also to stay informed and discuss new policy updates and regulations [3]. Governments and other organizations, such as the World Health Organization (WHO), have used social media as a direct communication channel to disseminate information and manage the crisis [4], [5]. COVID-19 is, until today, one of the most discussed topics on Twitter.…”