The study conducted semi-structured interviews with 31 early adopters of blockchain-based social media (BSM) platforms to understand their reasons for using these emerging platforms and to compare their usage with mainstream social media (MSM) platforms like Facebook and TikTok. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the manual content analysis of the interviews reveals that users’ adoption of BSM platforms is primarily motivated by social influence, financial incentives, and a desire to bypass the content moderation policies implemented by MSM. At the same time, the steep learning curve, security and privacy concerns hinder the widespread adoption of these platforms. Finally, the study validates the suitability of the UTAUT model for examining the adoption and use of BSM platforms, but it also proposes to include two new factors, namely financial incentives and content moderation.

• Information systems →Social networks; Internet communications tools.

UTAUT, Behavioral intention, Social networks, Blockchain-based social media (BSM), Decentralized platforms, Technology adoption, User experiences, Content moderation, Human computer interaction (HCI)

ACM Reference Format: Anatoliy Gruzd, Alyssa Saiphoo, and Philip Mai. 2023. Decentralizing Social Media: An Examination of Blockchain-based Social Media Adoption and Use based on the Unified Theory of Acceptance and Use of Technology (UTAUT): Blockchain-based Social Media Adoption and Use. In 33th ACM Conference on Hypertext and Social Media (HT ’23), September 4–8, 2023, Rome, Italy. ACM, New York, NY, USA, 2 pages. https://doi.org/10.1145/3603163.3609030

Mainstream social media platforms (MSM) like Facebook, YouTube, Instagram, and TikTok have become an essential part of our daily lives, serving various purposes such as connecting with friends, following celebrities, staying informed about current affairs, and accessing information about goods and services. However, concerns surrounding privacy breaches, the dissemination of misinformation, and even instances of individuals being de-platformed by social media companies have led some users to abandon these mainstream platforms [1, 3]. In response, some users are choosing to explore emerging de-centralized solutions for social networking and online publishing such as blockchain-based social media (BSM) platforms. To gain insight into why people use BSM platforms such as Steemit, Hive, and Minds, we conducted semi-structured interviews with a sample of early adopters. Our aim was to discover the reasons behind their decision to adopt and continue using these platforms. Two coders (two of the authors) analyzed the transcripts of the interviews to identify adoption and use factors, including those predicted by the Unified Theory of Acceptance and Use of Technology (UTAUT) model [2, 4].

Once the University Research Ethics Board granted approval, we invited current users of BSM platforms through social media posts on Twitter and Hive. Additionally, we utilized snowball sampling to expand the initial pool of participants. The interviews were conducted via the Zoom virtual meeting platform between June 16 and August 11, 2022. Areas of inquiry included how participants discovered BSM, their current platform preferences, and their engagement with MSM platforms. The complete set of questions can be found in the supplementary materials online. Following the interviews, two authors independently coded transcripts using NVivo (ver. 1.7) during the period of six months. The UTAUT model and its common extensions guided the analysis. Coding was done at the sentence level and double coding was used for statements referencing multiple factors. The coders resolved any coding disagreements by reviewing and discussing each other’s coding. Throughout the process, updates were made to the codebook and definitions as deemed necessary. At the end, the level of agreement between coders was high, with a Cohen’s kappa of 0.76 at the paragraph level and 0.71 at the sentence level. The final version of the codebook can be accessed online.

The sample consisted of 31 participants1, with the majority identifying as men (77%) and the remaining as women (23%). The largest age group represented was 25-34 years old (52%). About half of the participants were from Nigeria (48%), while 16% were from the United States. Among the participants, the most common highest level of education attained was a bachelor’s degree (48%). Self-employment was the most prevalent employment status (39%), followed by unemployment and actively seeking work (23%). Based on the content analysis, we found that the adoption and use patterns of our participants on BSM are in line with the UTAUT model and its common extensions. The factor most frequently mentioned by all 31 participants was Hedonic Motivation. All participants expressed their enjoyment of using BSM platforms, particularly when interacting with other community members. Additionally, most participants (25) appreciated the opportunity to learn about various topics, with a particular interest in cryptocurrencies. The second most frequently mentioned factor was Facilitating Conditions, which was referenced by all participants. It encompassed both positive and negative experiences with BSM. On the positive side, 18 participants appreciated the interface affordances provided by BSM, including the ability to access data stored on the same blockchain through different decentralized app (dApps). However, on the negative side, half of the participants expressed concerns about the lack of formal documentation and support available for new users of BSM. The third most frequently mentioned factor hindering the adoption and use of BSM was Effort Expectancy, according to 30 participants. These participants emphasized that navigating the platform required a significant amount of effort, especially during the initial onboarding phase. This difficulty was primarily due to a lack of prior knowledge about blockchains. Risks associated with using BSM and mentioned by 27 participants included potential scams, privacy and security breaches, and the possibility of a BSM platform going out of business. In contrast, 27 users highlighted Performance Expectancy as a factor that emphasized the perceived benefits of BSM. These benefits include increased usefulness and efficiency compared to MSM, especially for tasks such as organizing crowdsourcing initiatives or targeting a specific audience. Furthermore, 22 participants expressed Trust in BSM, whether it be in the developers, other users, or smart contracts. In terms of why users began using BSM, Social Influence emerged as the primary factor in learning about BSM initially. Of the participants, 27 mentioned that they started using BSM because someone in their personal network or an online influencer recommended it. Furthermore, Habit was identified by 27 participants as a key motivation for their ongoing use of one or multiple BSM platforms. In addition to the predictors outlined in the UTAUT model, our study revealed several other factors that affect the adoption and usage of BSM. Notably, all participants highlighted the role of Financial Incentives, such as the potential to earn reward tokens and cryptocurrency, as a major driving force behind their decision

1One participant did not consent for their interview to be recorded; therefore, their interview was not included in the content analysis.

to join a BSM platform. Another factor unique to BSM pertained to Content Moderation. A total of 24 participants expressed a positive view towards the absence of censorship on BSM platforms and emphasized the open access of these platforms.

The results confirmed that the UTAUT model and its common extensions are effective in predicting the key factors that influence the adoption and use of BSM platforms. Hedonic Motivation emerged as the most mentioned factor, with all participants expressing enjoyment of the platform and interaction with other users. Facilitating Conditions was also frequently mentioned; however, it encompassed both positive and negative experiences with the technology. Effort Expectancy was identified as a barrier to adoption due to the increased effort required, while Performance Expectancy was seen as a positive aspect, with users perceiving BSM as more helpful and efficient than MSM. Social Influence and Habit played a role in the initial decision and continued use of BSM platforms, respectively. Risk and Trust were also frequently discussed; participants exhibited trust in the technology despite the associated risks. The study also identified additional factors that influence the adoption and use of BSM platforms, which are not currently included in the UTAUT model as reported in the literature. These factors are Financial Incentives and Content Moderation. The integration with cryptocurrency sets BSM apart from MSM and offers users a new way to monetize their content and engagement. Content Moderation was another key factor, particularly for those dissatisfied with the moderation policies of MSM platforms. BSM platforms offer a decentralized approach with no single governing body controlling content moderation, which many participants saw as a positive aspect.

This research was funded in part by the Canada Research Chair program (PI: Gruzd). The authors thank all the participants who took part in the study, as well as the members of the Social Media Lab at Toronto Metropolitan University for their assistance in preparing the manuscript.

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