###### Abstract  
With increased obesity rates worldwide and the rising popularity in social media usage, we have witnessed a growth in hate speech towards fat/obese people. The severity of hate content has prompted researchers to study public perceptions that give rise to fat stigma from social media discourses. This article presents a systematic literature review of recent literature published in this domain to gauge the current state of research and identify possible research gaps. We have examined existing research (i.e., peer-reviewed articles that were systematically included using the EBSCO discovery service) to study their methodological aspects by reviewing their context, domain, analytical methods, techniques, tools, features and limitations. Our findings reveal that while recent studies have explored fat stigma content in social media, these mostly acquired manual analytical methods regardless of the evolved machine learning, natural language processing and deep learning methods. Although fat stigma in social media has gained enormous attention in current socio-psychological research, there exists a gap between how such research is conducted and what technologies are being applied, which limits in-depth investigations of fat stigma discussions. fat stigma; social media; overweight; obesity; analytical method; limitation +
Footnote †: journal: Medical  
The worldwide obesity rate has tripled since 1975; and it has been reported that in the year 2020, more than 2 billion adults have been classified as overweight of which 600 million are further classified as obese [6]. This data indicates obesity to be an ongoing problem. As such, social media discussions on obesity and associated topics are rampant and have caused much stigmatization of fat people. Fat stigma, or the social devaluation and denigration towards individuals considered to carry excessive weight [7], has been gathering momentum, which is reflected as hate speech targeting fat people. The connection between obesity and metabolic disorders [8] has fueled stigma discussions that have been further promoted by images of 'ideal' body shapes and sizes by mass media. Body image is described as cognitions, perceptions and attitudes towards one's appearance, which is reflected in how one ranks their bodily features within some measure of overall attractiveness level [9]. Therefore, when thinness is promoted by mass media as the ideal body size and shape, negative attitudes often prevail against people who do not fit within the thin classification. Studies have revealed the biological, psychological and sociological correlates associated with fat stigma studies in social media [10]; however, more studies are needed to decipher the technical details of how these correlates were discovered. Various text mining and machine learning methods including sentiment analysis, topic modeling, emotion analysis and co-occurrence analysis have been implemented in hate speech detection and classification studies e.g., [11; 12; 13], etc. These technical methods promote the investigation of large amounts of textual data which assist in unravelling the stigmatizing information that is embedded in the social media discussions. As social media discourses on obesity evolve, examining the methodological approaches used for analysing obesity content in prior literature has enabled us gauge the current state of research in this field of study. Accordingly, the primary research question posed in this study is:  
What are the trends in the application of technical and methodological approaches for detecting fat stigma in social media settings? A review of methods used in prior research studies for identifying fat stigma content expressed over social media has been conducted to answer this research question. Following a systematic literature review approach, we provide an overview of fat stigma studies that have been published in the last decade.