When Do Likes Create Bias?

The rise of online communities has ushered in a new era of content sharing with platforms that serve many functions and overcome the geographic and synchronous limitations of traditional word-of-mouth communications. Community-based question answering sites (CQA) have emerged as convenient platforms for users to exchange knowledge and opinions with others. Research on CQA has primarily focused on engaging members to voluntarily contribute to these communities. Helpfulness ratings and “likes” are one mechanism platforms can use to engage members, but these subjective evaluations can also create bias. In this ERF paper, the elaboration likelihood model is applied to better understand when bias can occur with these platforms. An experimental design and a planned data collection are reported

Can AI Moderate Online Communities?

The task of cultivating healthy communication in online communities becomes increasingly urgent, as gaming and social media experiences become progressively more immersive and life-like. We approach the challenge of moderating online communities by training student models using a large language model (LLM). We use zero-shot learning models to distill and expand datasets followed by a few-shot learning and a fine-tuning approach, leveraging open-access generative pre-trained transformer models (GPT) from OpenAI. Our preliminary findings suggest, that when properly trained, LLMs can excel in identifying actor intentions, moderating toxic comments, and rewarding positive contributions. The student models perform above-expectation in non-contextual assignments such as identifying classically toxic behavior and perform sufficiently on contextual assignments such as identifying positive contributions to online discourse. Further, using open-access models like OpenAI's GPT we experience a step-change in the development process for what has historically been a complex modeling task. We contribute to the information system (IS) discourse with a rapid development framework on the application of generative AI in content online moderation and management of culture in decentralized, pseudonymous communities by providing a sample model suite of industrial-ready generative AI models based on open-access LLMs

Social Media Influencers: Talk is Not Cheap!

Social media influencers are digital opinion leaders who have amassed large followings on social media. Through their content and communication on social commerce platforms, and social networking sites, social media influencers can influence their audience\u27s attitude towards brands and encourage purchase decisions. This paper explores the impact of social media influencers on the relationship between social commerce and purchase intention. Since the relationship between social commerce and purchase intention has been thoroughly examined by researchers, I discover through reviewing the literature how an independent entity can impact social media consumers\u27 attitudes and purchase decisions. Specifically, I analyze the social commerce construct and develop propositions related to the relationships between the dimensions of social commerce and the social media influencer construct

Building Organizational Knowledge Quality: Investigating the Role of Social Media and Social Capital

To the extent that knowledge is the most strategically important resource for sustainable competitive advantage, organizations must consciously and systematically manage their knowledge asset. In this paper, we explore how social media and social capital at organizational level help organizations benefit from their knowledge management initiatives through improving organizational knowledge quality. A research model was developed and survey data were used to test the model. The preliminary results show that social media helps to provide the technical environment conducive to knowledge exchange and social capital enables the actual knowledge sharing between businesses. Both facilitate an organizational emphasis on knowledge management, which leads to organizational knowledge of higher quality

Strategic Digital Campaign to Improve Rural Health Workers Recruitment Process in Indonesia

With current geographical disparities, Indonesia's ratio of general practitioners (GPs) to population is still lower than the WHO-recommended figure. The Center for Indonesia's Strategic Initiatives (CISDI) initiated Pencerah Nusantara (PN), a team-based young health workers deployment program to rural areas to improve the distribution of human resources for health including GPs, nurses, midwives, public health specialists, and health advocates. Entering PN's sixth year of implementation, aimed to attract more application from young health workers, particularly of GPs, CISDI employed strategic digital campaign involving strategic content development, strategic content channeling and strategic content promotion; as an intervention to improve the recruitment process of PN Batch 6. This paper investigates whether the intervention manages to improve the recruitment process of PN and mainly using secondary data such as “Relative Volume Search” measuring Google search popularity, social media insights measuring social media engagement and Google Analytics of PN weblog measuring weblog visits and online recruitment data measuring PN daily application rate from 2016 and 2017. Following the intervention, Google search popularity was doubled, social media engagement showed improvement range from 153 percent to 1,813 percent and PN daily application rate increased 148 percent of health workers and 192 percent of GP, compared to 32 percent and 44 percent of 2016 accordingly. A specifically targeted digital campaign implemented substantially improved recruitment promotion indicated by the significant growth of PN daily application rate.&nbsp

Impact of Informational Social Support and Familiarity on Social Commerce Intention

Due to the increased popularity of social networking sites, a new platform called social commerce has emerged. Social commerce facilitates online interactions and user contributions to assist them in conducting commercial transactions. In this paper, we explore and identify factors that affect the intention to adopt social commerce. This study develops a comprehensive social commerce framework that has five key variables: Reviews and recommendations on social networking sites, customer ratings on social networking sites, trust on social networking sites, brand familiarity, and social commerce platform familiarity. Data were obtained from a survey of 310 consumers and were analyzed using Partial Least Squares PLS. The results indicate that reviews and recommendations on social networking sites, customer ratings on social networking sites, trust on social networking sites, and brand familiarity have a positive and direct influence on social commerce intention, while social commerce platform familiarity is not significant. This study contributes to consumer behavior theory by applying predictors of intention to social commerce for traditional e-commerce sites. The results also help e-commerce practitioners to improve their use of social tools

Impact of Informational Social Support and Familiarity on Social Commerce Intention

Due to the increased popularity of social networking sites, a new platform called social commerce has emerged. Social commerce facilitates online interactions and user contributions to assist them in conducting commercial transactions. In this paper, we explore and identify factors that affect the intention to adopt social commerce. This study develops a comprehensive social commerce framework that has five key variables: Reviews and recommendations on social networking sites, customer ratings on social networking sites, trust on social networking sites, brand familiarity, and social commerce platform familiarity. Data were obtained from a survey of 310 consumers and were analyzed using Partial Least Squares PLS. The results indicate that reviews and recommendations on social networking sites, customer ratings on social networking sites, trust on social networking sites, and brand familiarity have a positive and direct influence on social commerce intention, while social commerce platform familiarity is not significant. This study contributes to consumer behavior theory by applying predictors of intention to social commerce for traditional e-commerce sites. The results also help e-commerce practitioners to improve their use of social tools

Peran Social Support Terhadap Relationship Quality Dan Social Commerce Intention

In the era of social commerce, individuals share their knowledge,experience, and information about products and services with people in theirneighborhood or close friends. Formed on the basis of social support theory,relationship quality, and social media concepts, this study proposes a model thataims to investigate or analyze more deeply about the role of social factors thatinfluence relationship quality with its three dimensions (commitment, trust andsatisfaction), as well as social commerce intention. Surveys were conducted usingonline-survey platforms and questionnaires distributed on which are the mostpopular social networking sites in Indonesia (APJII, 2016), and the PLS-SEMmethod was used to prove empirically the proposed model. The results of thisstudy related to social factors that give a significant influence on relationshipquality and social commerce intention. This study highlights the changingbehavior of consumers in the era of social commerce. It also contributespositively to the development of theory in the context of social commerce.Practically, the results of this study indicate that technology changes in the ecommerceis a new opportunity and challenge for practitioners to be able toadjust and take advantage of these opportunities

What Drives User Contribution in an Online Community? A Study in Contributor Influence and User Status

Online communities (OC’s) depend on shared interests and user interactions mediated by technology. Successful OC’s find ways to encourage these interactions to grow communities. Many OC’s have influential users that help grow the community by their very presence and contributions. However, the process for identifying users having the greatest impact is not trivial. This study offers a new method for identifying these influential users through the creation of modified Hirsch indices, which improves upon the current method of using contribution counts or a survey method of polling other users. We validate the new measures against user status and then analyze the measures by correlating them against postings, thread starts, and views and replies to the thread starts for a shared interest OC

Social Media in Healthcare

Despite its significant potential there has been limited analysis of the use of interactive social media in a healthcare setting. This paper considers important feedback and advice from cancer patients at a large Canadian academic health science centre, along with a review of Social Media literature, Information Seeking Theory, Virtual Communities literature, Social Theory, Adaptive Structuration Theory (AST), and technology evolution to propose a high-level, theoretical interactive-dynamic social media platform for cancer patients. Further, it puts forward a research question and four propositions to guide future empirical research to assess whether this type of social media platform positively influences patient and provider satisfaction, health outcomes and value for money in the treatment of cancer patients