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By examining types of literacies taught by public libraries and the modes through which these programs were offered, this study aims to explore how public libraries might integrate data literacy training for the general public into existing library educational programs.

This study examined programs offered in 30 US public libraries during 2019 and 2020 to better understand types of literacy education announced to the public through library website listings and Facebook Events pages.

While public libraries offered educational programs in literacy areas ranging from basic reading and writing to technology, vocational skills, health literacy and more, data literacy training was not widely offered. However, this study identified many already-existing programs highly compatible for integrating with data literacy training.

This study offered new insights into both the literacies taught in public library programs as well as ways for public libraries to integrate data literacy training into existing educational programming, in order to better provide data literacy education for the general public.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

In the online environment, consumers increasingly feel vulnerable due to firms’ expanding capabilities of collecting and using their data in an unsanctioned manner. Drawing from gossip theory, this research focuses on two key suppressors of consumer vulnerability: transparency and control. Previous studies conceptualize transparency and control from rationalistic approaches that overlook individual experiences and present a unidimensional conceptualization. This research aims to understand how individuals interpret transparency and control concerning privacy vulnerability in the online environment. Additionally, it explores strategic approaches to communicating the value of transparency and control.

An interpretivism paradigm and phenomenology were adopted in the research design. Data were collected through semi-structured interviews with 41 participants, including consumers and experts, and analyzed through thematic analysis.

The findings identify key conceptual dimensions of transparency and control by adapting justice theory. They also reveal that firms can communicate assurance, functional, technical and social values of transparency and control to address consumer vulnerability.

This research makes the following contributions to the data privacy literature. The findings exhibit multidimensional and comprehensive conceptualizations of transparency and control, including user, firm and information perspectives. Additionally, the conceptual framework combines empirical insights from both experiencers and observers to offer an understanding of how transparency and control serve as justice mechanisms to effectively tackle the issue of unsanctioned transmission of personal information and subsequently address vulnerability. Lastly, the findings provide strategic approaches to communicating the value of transparency and control.

The primary objective was to develop a user-centered mobile health application (app) tailored to the specific health information needs of among immigrant women from diverse backgrounds in Korea.

In-depth interviews were conducted with 24 immigrant women to gain insights into their health information-seeking behavior. Based on the findings, a mobile app was designed and developed. A beta version of the app underwent validation by an MD and seven expert reviewers who assessed the app for content accuracy and conformance to mobile heuristics. Last, immigrant women (n = 12) evaluated the usability of the app.

The study revealed that the interviewed immigrant women had strong health information needs related to pregnancy and parenting. Most of them used multiple sources to find and verify health information. Language barriers were identified as a major obstacle to accessing and evaluating health information. The results of the user test indicated that the app effectively facilitated study participants' search for reliable health information, meeting their specific needs.

This research extended the literature by addressing the limited availability of mobile apps tailored to the health information needs of immigrant women in Korea.

By incorporating multilingual support and focusing on pregnancy and parenting information, the health app serves as a valuable tool to bridge the gap in health information access and to facilitate the well-being of immigrant women in the country.

This study aims to understand the extent of privacy concerns regarding voice-activated personal assistants (VAPAs) on Twitter. It investigates three key areas: (1) the effect of privacy-related press coverage on public sentiment and discussion volume; (2) the comparative negativity of privacy-focused conversations versus general conversations; and (3) the specific privacy-related topics that arise most frequently and their impact on sentiment and discussion volume.

A dataset of 441,427 tweets mentioning Amazon Alexa, Google Assistant, and Apple Siri from July 1, 2019 to June 30, 2021 were collected. Privacy-related press coverage has also been monitored. Sentiment analysis was conducted using the dictionary-based software LIWC and VADER, whereas text mining packages in R were used to identify privacy-related issues.

Negative privacy-related news significantly increases both negativity and volume in Twitter conversations, whereas positive news only boosts volume. Privacy-related tweets were notably more negative than general tweets. Specific keywords were found to either increase or decrease the sentiment and discussion volume. Additionally, a temporal evolution in sentiment, with general attitudes toward VAPAs becoming more positive, but privacy-specific discussions becoming more negative was observed.

This research augments the existing online privacy literature by employing text mining methodologies to gauge consumer sentiments regarding privacy concerns linked to VAPAs, a topic currently underexplored. Furthermore, this research uniquely integrates established theories from privacy calculus and social contract theory to deepen our analysis.

This research examines the relationship between the timeliness in announcing the discovery of a data breach and consumer trust in an e-commerce company, as well as later trust-rebuilding efforts taken by the company to compensate users impacted by the breach.

A survey experiment was used to examine the effect of both trust-reducing events (announced data breaches) and trust-enhancing events (provision of identity theft protection and credit monitoring) on consumer trust. The timeliness of the breach announcement by an e-commerce company was manipulated between two randomly assigned groups of subjects; one group viewed an announcement of the breach immediately upon its discovery, and the other viewed an announcement made two months after the breach was discovered. Consumer trust was measured before the breach, after the breach was announced, and finally, after the announcement of data protection.

The results suggest that companies that delay a data breach announcement are likely to suffer a larger drop in consumer trust than those that immediately disclose the data breach. The results also suggest that trust can be repaired by providing data protection. However, even after providing identity theft protection and credit monitoring, companies that fail to promptly disclose a breach have lower repaired trust than companies that promptly disclose.

This study contributes to the literature on e-commerce trust by examining how a company's forthrightness in reporting a data breach impacts user trust at the time of the disclosure of the data breach and after subsequent efforts to repair trust.