Content Analysis of Social Media: A Grounded Theory Approach

ABSTRACTSocial media has become a vital part of social life. It affects the beliefs, values, and attitudes of people, as well as their intentions and behaviors. Meanwhile, social media enables governments and organizations to engage people while allowing consumers to make informed decisions. Therefore, converting social media content into information, key concepts, and themes is crucial for generating knowledge and formulating strategies. In this paper, we introduce a grounded theory approach that involves (i) defining the goal and scope of a study; (ii) logically and systematically identifying social media sources, total sample size, and the sample size of every source category; (iii) employing computer-aided lexical analysis with statistical and graphical methods to identify the key dimensions of the topic while minimizing human errors, as well as coding and categorization biases; and (iv) interpreting the findings of the study. This systematic approach was illustrated with the destination image of Macao as an example. The proposed methodology with its hybrid nature can quantitatively analyze qualitative social media content (e.g., impressions, opinions, and feelings) and can identify emergent concepts from the ground up. This paper contributes to electronic commerce research by presenting a novel approach for extracting, analyzing, and understanding social media content.Keywords: Social media; Content analysis; Lexical and statistical approaches; Concept formation(ProQuest: ... denotes formulae omitted.)1. IntroductionThe Internet has attracted the attention of research communities [Comley, 2008; Dwivedi et al., 2008; Zwass, 1996]. In particular, the significant role of analyzing social media and networks to advance our understanding of information sharing, communication [Averya et al., 2010; Chiu et al., 2006; Turri et al., 2013], opinion formation, and dissemination has been recognized [Abrahams et al., 2012; Airoldi et al., 2006; Bai, 2011; Jansen et al., 2011; Lane et al., 2012]. Nevertheless, rigorous, quantitative studies on social media content, particularly on electronic commerce and information management, remain scarce [Bai, 2011]. The most considerable barrier to social media usage is the lack of a versatile methodology for selecting, collecting, processing, and analyzing conte xtual information obtained from social media sites. However, several software companies have developed proprietary text mining systems for data visualization [Arnold, 2012], and researchers have developed expert systems for sentiment analysis [Abrahams et al., 2012; Lane et al., 2012].Nevertheless, social media content is widely accessible, up-to-date, and available in electronic format. Therefore, a systematic approach is necessary, as it helps electronic commerce researchers, organizations, and governments understand the commonality in various online text data that appear in social media. Using the information obtained from social media, researchers can gain valuable insights into the beliefs, values, attitudes, and perceptions of social media users with regard to the utility of user-generated content and trust formation [Karimov et al., 2011; Kim et al., 2012; Wang & Li, 2014]. Consequently, such information can help marketers monitor the perceptions of people regarding social networks and aid organizations in strategic planning.To address the gap between the availability of user-generated raw text and the contextual information of aggregated data, the present study introduces a grounded theory approach [Strauss & Corbin, 1988] to analyze social media content to identify the underlying factor structure of the collected information and to interpret the identified structure in relation to the study objective. Strauss and Corbin [1998] defined the grounded theory approach as a research method that employs a systematic set of procedures to develop an inductively derived grounded theory about a particular phenomenon. …