Greenwashing, the phenomenon of companies misleading consumers about their sustainability practices, is prevalent in the fashion industry. This study explores consumer opinions on greenwashing through analysis of social media discourse. Cognitive dissonance theory served as the theoretical framework, explaining how consumers reconcile conflicting information about brands’ sustainability claims. In Study 1, 446 comments on 12 Reddit posts were collected using the search term “fashion greenwashing”. Using the Latent Dirichlet Allocation (LDA) algorithm and manual review, we identified three major themes: the phenomenon of fashion greenwashing, consumer empowerment in sustainable fashion, and skepticism towards fast fashion brands’ marketing strategies. In Study 2, using the search term, “#fashiongreenwashing”, two researchers collected and analyzed 76 Instagram posts with 370 comments. A manual review was employed to extract major themes, and network graphs of caption tags within the same theme were constructed. Three major themes emerged: strategies to combat fashion greenwashing, examples of fashion greenwashing, and advocacy and regulation in sustainable fashion. Findings from Studies 1 and 2 revealed that consumers are increasingly aware of brands’ deceptive practices and advocacy for sustainable practices to resolve this dissonance when they see greenwashing information. This study underscored the need for fashion brands to provide transparent and authentic information.

"Greenwashing" is a term that describes the phenomenon of companies misleading consumers about the environmental benefits of their products or their commitment to sustainability to increase profit (Slater, 2019; Watson, 2016). Recently, the fashion industry has been chosen as one of greenwashing's worst offenders (Webb, 2021). Fashion brands benefit from greenwashing by charging a premium for "Sustainable" products. In addition, the global fashion industry is growing tremendously (Pinnock, 2021), producing over 100 billion tons of clothing yearly, approximately twenty percent of which goes unsold (Thomas, 2019). Greenwashing has harmful consequences for both consumers and the environment. Socially conscious consumers can be manipulated by fashion brands' greenwashing. There are several reasons the fashion industry is vulnerable to greenwashing. One is the increase in sustainability awareness among the Millennial and Gen Z generations. They are willing to pay more for sustainable products, especially fashion items. The others include the fashion industry's complex supply chain and lack of regulations (West, 2023). Recently, awareness of greenwashing has increased, and it has been discussed among consumers more frequently. Therefore, it is necessary to examine the current consumers' opinions regarding greenwashing in fashion brands. The cognitive dissonance theory originally developed by Festinger (1957) is utilized in this study as a theoretical framework. According to this theory, when individuals initially accept green claims from fashion companies and later encounter information that contradicts these claims, they experience cognitive dissonance, leading to an internal conflict. To alleviate this discomfort and resolve the dissonance, individuals may adopt various strategies, for example, they might change their purchasing decisions, justify their previous choices, or alter their perception of the brand's sustainability claims. The cognitive dissonance theory has been utilized to investigate the effects of various degrees of greenwashing on fashion brands' reputation (De Jong et al, 2020). In this study, the cognitive dissonance theory serves as a framework to interpret how consumers psychologically manage the inconsistencies between their sustainability values and the greenwashing actions of fashion brands. In this study, Reddit was chosen as the data source due to its extensive user base, which engages in detailed discussions on fashion greenwashing. To get the relevant data, we used the search term "fashion greenwashing" to identify pertinent posts and comments on Reddit platform. Only posts that have a minimum of five comments were considered for analysis to ensure a sufficient depth of discussion. Overall, 446 comments from 12 distinct posts were collected using Python on Feb 28, 2024. The widely adopted topic modeling method, Latent Dirichlet Allocation (LDA) algorithms (Blein et al., 2023), were utilized to extract the topics from these comments. Given the relatively modest size of the dataset, it was feasible to manually review the content of the textual data. This dual-method approach allowed for a thorough