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In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

The struggle for racial justice has always faced significant challenges and controversies across interpersonal, intergroup and structural levels. As racism continues to evolve and adapt to new social, political and technological developments, researchers, activists and practitioners grapple with complex and intersecting issues. This chapter discusses some of the ongoing challenges anti-racist endeavours face today. It engages with contemporary global issues, such as international migration, globalisation and the digital revolution that have implications on the fight against racism. The chapter covers topics such as the recent backlashes against anti-racism, the emergence of the ‘colour-blind’ ideology and the challenges anti-racism faces in the realm of technological advance and digital spaces. Additionally, this chapter explores the discourse of decolonisation as a radical approach to anti-racism. It concludes with a critical discussion of the idea that mainstreaming and expanding anti-racism to include racial majorities may enhance its effectiveness.

This paper presents results from a participatory action research study with 46 LGBTQIA+ community leaders and 60 library workers who participated in four community forums at public libraries across the US. The forums identified barriers to LGBTQIA+ communities addressing their health questions and concerns and explored strategies for public libraries to tackle them.

Forums followed the World Café format to facilitate collaborative knowledge development and promote participant-led change. Data sources included collaborative notes taken by participants and observational researcher notes. Data analysis consisted of emic/etic qualitative coding.

Results revealed that barriers experienced by LGBTQIA+ communities are structurally and socially entrenched and require systematic changes. Public libraries must expand their strategies beyond collection development and one-off programming to meet these requirements. Suggested strategies include outreach and community engagement and mutual aid initiatives characterized by explicit advocacy for LGBTQIA+ communities and community organizing approaches.

Limitations include the sample's lack of racial diversity and the gap in the data collection period between forums due to COVID-19. Public libraries can readily adopt strategies overviewed in this paper for LGBTQIA+ health promotion.

This research used a unique methodology within the Library and Information Science (LIS) field to engage LGBTQIA+ community leaders and library workers in conversations about how public libraries can contribute to LGBTQIA+ health promotion. Prior research has often captured these perspectives separately. Uniting the groups facilitated understanding of each other's strengths and challenges, identifying strategies more relevant than asking either group alone.

This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.

Based on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.

The authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.

This paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.

This paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.

The social media industry has entered a new stage with intensifying competition and heightened uncertainty about future directions. The purpose of this paper is to provide analyses of the current challenges and to identify industry-wide trends that may offer a roadmap for the future.

Drawing on publicly available key performance metrics, company reports and press reports, this paper offers critical analyses of the challenges facing the major social media platforms and new trends in the social media industry.

This study identified five major trends in the current social media industry: 1) content is king, and that content is moving to visual; 2) artificial intelligence is key to competitive advantage; 3) network effects still matter, but business model innovation can overcome that barrier; 4) the need to broaden revenue sources; and 5) the strive for the everything app. In this changing environment, social media companies need to adapt and innovate their business models proactively to stay ahead.

This paper not only sheds light on the current challenges of individual social media platforms but also identifies industry-wide trends that may apply across all platforms. Taken together, these insights paint a comprehensive picture of the current industry landscape, as well as offer clues about its future directions.

This paper aims to center the experiences of three cohorts (n = 40) of Black high school students who participated in a critical race technology course that exposed anti-blackness as the organizing logic and default setting of digital and artificially intelligent technology. This paper centers the voices, experiences and technological innovations of the students, and in doing so, introduces a new type of digital literacy: critical race algorithmic literacy.

Data for this study include student interviews (called “talk backs”), journal reflections and final technology presentations.

Broadly, the data suggests that critical race algorithmic literacies prepare Black students to critically read the algorithmic word (e.g. data, code, machine learning models, etc.) so that they can not only resist and survive, but also rebuild and reimagine the algorithmic world.

While critical race media literacy draws upon critical race theory in education – a theorization of race, and a critique of white supremacy and multiculturalism in schools – critical race algorithmic literacy is rooted in critical race technology theory, which is a theorization of blackness as a technology and a critique of algorithmic anti-blackness as the organizing logic of schools and AI systems.