The rise in adoption of cryptoassets has brought many new and inexperienced investors in the cryptocurrency space. These investors can be disproportionally influenced by information they receive online, and particularly from social media. This paper presents a dataset of crypto-related bounty events and the users that participate in them. These events coordinate social media campaigns to create artificial "hype" around a crypto project in order to influence the price of its token. The dataset consists of information about 15.8K cross-media bounty events, 185K participants, 10M forum comments and 82M social media URLs collected from the Bounties(Altcoins) subforum of the BitcoinTalk online forum from May 2014 to December 2022. We describe the data collection and the data processing methods employed and we present a basic characterization of the dataset. Furthermore, we discuss potential research opportunities afforded by the dataset across many disciplines and we highlight potential novel insights into how the cryptocurrency industry operates and how it interacts with its audience.

Technological advances in the smart home have created new opportunities for supporting digital citizens’ well-being and facilitating their empowerment but have enabled new types of complex online harms to develop. Recent statistics have indicated that ‘smart’ technology ownership increases yearly, driven by lower costs and increased accessibility. Research on smart homes has also grown, focusing on technology perspectives at the expense of a user-centric approach sensitive to the smart home’s harms, risks, and vulnerabilities. This scoping review addresses the information gap by underscoring the scope of literature that exists regarding complex online harms, vulnerabilities, and risks associated with smart home technologies and citizens’ agency. The goal is to understand the state of knowledge, gaps in the literature, and areas for future study. The importance and originality of this paper lie in its interdisciplinary review and approach. It is hoped that this research will contribute to a deeper understanding of complex online harms in the smart home. Three online databases were utilised to identify papers published between 2017 and 2022, from which we selected 235 publications written in English that addressed harms, risks, vulnerabilities, and agency in the smart home context. This allowed us to map contemporary literature to reveal significant gaps in our understanding of the complex online harms affecting smart home users and identify opportunities for further research. This review identified emerging themes of ‘risks’, ‘vulnerabilities’, and ‘harms’ in that order of frequency within the literature on smart homes. The usage of terms is skewed towards computing science and information security, which comprised the majority of the literature at 54.6%. Human–computer interaction papers contributed 24.4%, while social sciences accounted for 16.2%. Risks, harms and vulnerabilities within smart home ecosystems and IoTs are ongoing issues with complexities that necessitate research. Privacy, security, and well-being are key themes that embody the scope of complex harms affecting smart home devices in the broad literature. This review establishes disciplinary research gaps, especially in user-centred perspectives, due to a heavy technology focus in the existing literature. Therefore, further research is needed to address emergent risks, harms and vulnerabilities of smart home devices and understand how user agency and autonomy can complement the design, interface, and socio-technical aspects of smart home systems.

Smart home device usage is increasing, as is the diversity of users and range of devices. Additionally, it is becoming increasingly common to interconnect devices (e.g., via trigger-action rules) which, while bringing benefits, can bring unforeseen security and privacy risks. Developing strategies to protect users as well as understanding what biographical or attitudinal characteristics contribute to these risks is a critical step for ensuring empowered, but safe, interconnected smart device usage. Using narrative descriptions of domestic smart devices, two experiments explored how the prevailing security/privacy contexts—priming conditions—in which 20 trigger-action rules (developed via a Delphi Study) were presented influenced the adoption of rules favoring either security or privacy. Both experiments contrasted three priming conditions: no prime, security prime, privacy prime. Experiment 1 (n = 254) used explicit priming, giving direct instruction to maximize a security or privacy outcome while Experiment 2 (n = 325) used implicit priming, with an apparently unrelated security or privacy problem-solving puzzle. Across both experiments, priming promoted safer rule adoption, markedly so when explicit. Explicit priming produced an asymmetry however: privacy priming improved privacy scores with security scores unchanged and security primes improved security scores while worsening privacy scores. Across experiments, two dimensions of user attitudes shaped riskier rule choice: perceived benefits of technology and pre-existing trusting beliefs in online companies. Our novel findings reveal that implicit and explicit priming shape safe use of trigger-action rules in domestic settings and that age, perceived trust and perceived benefits should be considered when designing safety messaging.

Individuals share a diversity of content on social media for a variety of reasons. Research has often described and explained disclosure via the application of a subjective cost–benefit analysis framed around reciprocity, suggesting that people communicate selfishly motivated by the expectation of receiving something in return. This paper investigates the moderating effects of tie strength and interpersonal trust on the relationship between expected reciprocity and intensity of communication between two social media connections. A Facebook application presented participants with a random set of their friends and asked them to rate their friendships in terms of these values. Overall, 90 participants rated 1728 friendships, while the application collected 11 activity variables depicting the actual communication that has taken place in each pair of connections. A principal component analysis was used to distinguish between text- and photograph-related communication, and two moderated multiple regressions were conducted to establish the moderating effects. The results show significant moderating effects of tie strength and trust on the communication around photographs, but not around text. This study contributes to communication research by explicating the ways that tie strength and trust affect patterns of communication on social media. Implications for social media researchers and designers are discussed.

Social Network Sites (SNSs) are fundamentally changing the way humans connect, communicate, and relate to one another and have attracted a considerable amount of research attention. In general, two distinct research approaches have been followed in the pursuit of results in this research area. Firstly, established traditional social science methods, such as surveys and interviews, have been extensively used for inquiry-based research on SNSs. More recently, however, the advent of Application Programming Interfaces (APIs) has enabled data-centric approaches that have culminated in theory-free “big data” studies. Both of these approaches have advantages, disadvantages and limitations that need to be considered in SNS studies. This PhD work proposes that a suitable combination of these two approaches can help understand the limitations and address the shortcomings that researchers are faced with when following each approach separately. In order to illustrate the practicability and value of this combination of approaches, I propose to employ usage and network data collected via an API to complement survey metrics in two SNS studies. The first study examines the motivations for using Facebook and Twitter, in order to enhance our understanding of how and why people use these services, while the second study focuses on aspects of the interpersonal relationships on Facebook, such as tie strength, trust and information disclosure.

This study explores the links between motives for using a social network service and numerical measures of that activity. Specifically, it identified motives for Facebook use by employing a Uses and Gratifications (U&G) approach and then investigated the extent to which these motives can be predicted through usage and network metrics collected automatically via the Facebook API. In total, 11 Facebook usage metrics and eight personal network metrics served as predictors. Results showed that all three variable types in this expanded U&G frame of analysis (covering social antecedents, usage metrics, and personal network metrics) effectively predicted motives and highlighted interesting behaviors. To further illustrate the power of this framework, the intricate nature of privacy in social media was explored and relationships drawn between privacy attitudes (and acts) and measures of use and network structure.

This paper explores uses and gratifications of a content community on a social network service - a music video sharing group on Facebook. In a two-stage study, 20 users first generated words or phrases to describe how they used the group, and what they enjoyed about their use. These phrases were coded into 34 questionnaire items that were then completed by 57 new participants. Factor analysis on this data revealed four gratifications: contribution; discovery; social interaction and entertainment. These factors are interpreted and discussed, leading to design implications and guidelines aimed at informing the design of future online services that combine media sharing with social interaction to create online systems based on a rich and meaningful object-centered sociality.

This paper presents a multi-pronged study of users' location-sharing practices in the context of online social networks. The contribution of this study is two-fold: first it presents a series of insights relating to location-sharing practices, and second it highlights the use of third-person scenarios as a useful method for eliciting privacy concerns and potentially educating users.