Novel Directions for Multiagent Trust Modeling in Online Social Networks

This thesis presents two works with the shared goal of improving the capacity of multiagent trust modeling to be applied to social networks. The first demonstrates how analyzing the responses to content on a discussion forum can be used to detect certain types of undesirable behaviour. This technique can be used to extract quantified representations of the impact agents are having on the community, a critical component for trust modeling. The second work expands on the technique of multi-faceted trust modeling, determining whether a clustering step designed to group agents by similarity can improve the performance of trust link predictors. Specifically, we hypothesize that learning a distinct model for each cluster of similar users will result in more personalized, and therefore more accurate, predictions. Online social networks have exploded in popularity over the course of the last decade, becoming a central source of information and entertainment for millions of users. This radical democratization of the flow of information, while purporting many benefits, also raises a raft of new issues. These networks have proven to be a potent medium for the spread of misinformation and rumors, may contribute to the radicalization of communities, and are vulnerable to deliberate manipulation by bad actors. In this thesis, our primary aim is to examine content recommendation on social media through the lens of trust modeling. The central supposition along this path is that the behaviors of content creators and the consumers of their content can be fit into the trust modeling framework, supporting recommendations of content from creators who not only are popular, but have the support of trustworthy users and are trustworthy themselves. This research direction shows promise for tackling many of the issues we've mentioned. Our works show that a machine learning model can predict certain types of anti-social behaviour in a discussion starting comment solely on the basis of analyzing replies to that comment with accuracy in the range of 70% to 80%. Further, we show that a clustering based approach to personalization for multi-faceted trust models can increase accuracy on a down-stream trust aware item recommendation task, evaluated on a large data set of Yelp users

How Airbnb Conveys Social and Economic Value through User Representation

New platforms for renting and sharing among private individuals are emerging in today’s e-commerce landscape. Airbnb can be regarded as a representative of many such platforms. Such accommodation rental commonly implies shared usage where both host and guest occupy a space at the same time, involving social interactions that can provide additional value. Drawing on social reward theory, this paper proposes a research model that links the guest’s intention to book to the host’s user representa-tion via the pathways of social and economic value. We propose a design to evaluate our research model by means of a scenario-based online experiment, including the common elements of user repre-sentation (1) text reviews, (2) profile information (e.g., occupation, hobbies and interests), (3) star rating, and (4) the listing price. With this, we expect to contribute to a better understanding of the driving factors behind guests’ booking decisions in accommodation sharing

Who do people trust for financial advice? Iowans rate the credibility of information channels for financial information

This study aims to determine the channels Iowans find trustworthy and expert in providing information regarding financial matters. It also examines how perceptions of trust and expertise relate to people\u27s assessment of their financial literacy. Data were gathered through an online survey of 207 adults. The results show that Iowans made the most use of family and friends, community banks and credit unions, and newspapers. They rated national banks, websites, and government agencies as offering the most useful information. The most trusted sources were family members and third-party consultants and advisors, community banks and credit unions, and the banks they currently use. The sources seen as most expert were consultants and advisors, community banks and credit unions, and the banks they patronize. Perceived level of financial literacy had a bearing on the credibility estimates for seven of the 11 sources of financial information

Analyzing Australian SME Instagram Engagement via Web Scraping

Background: Social media has grown into a prominent marketing and communication tool, and Instagram is a leader in this regard due to its distinctive supports for medial rich contents. Due to the challenges faced by Small-and-medium-enterprises (SMEs), they are suggested to embrace social media technology. Previous studies in Interactive value creation theory (IVF) indicated that SMEs-followers co-creation processes enable Instagram engagement. However, little is known of how to promote the value co-creation process via practical Instagram micro-practices that SMEs can employ regarding their constraints. This study is among the first to examine SMEs\u27 practices for Instagram engagement via the process of value co-creation. Method: We collected data regarding Instagram engagements of 10 Australian SMEs in eight months period using Instagram API. Qualitative analysis is conducted based on 2110 contents in a Poisson regression model. Content analysis and time-series visualizations are employed to investigate the uniqueness of several outliners in the dataset. Results: Findings imply that SMEs should bank on @Tagging instead of #Hashtags to get more engagement as contents with @Tagging show higher levels of inclusiveness and trustworthiness. Also, customized postings for the loci-specific audience effectively encourage followers to participate in conversations, while commercial intensive posting style shows adverse effects due to its low level of credibility. Rich media contents would not necessarily reel in more engagement; the commitment and consistent postings amassed a considerable number of followers over time, leading to a higher engagement rate. Conclusions: This study confirmed the benefits of data scraping in building business intelligence and validate the IVF framework as the theoretical background to investigate the effectiveness of Instagram micro-practices. IVF should be considered in designing social media practices to enable SMEs and followers\u27 collaborations for business value generation. This study provides extra interpretations of the interrelationships between IVF, visual-rich contents, and social media engagement

The Effectiveness of Social Media Communications for Visitor Behaviour Management in Ontario's Parks and Protected Areas

Parks and protected areas in Ontario have long been bastions of conservation while also providing critical outdoor recreation opportunities for the health and well-being of the people. This was particularly evident during the early stages of the COVID-19 pandemic, where parks and protected areas agencies around the world experienced drastic increases in visitation as people sought opportunities to spend time in the natural world. However, the balance of environmental conservation and the provision of outdoor recreation opportunities are often seen as competing interests given the potential degradation that is associated with human use of these natural spaces. As a result, it is crucial for park managers and protected areas agencies to mitigate negative visitor behaviour issues as much as possible. Communications in their various formats (signage, in-person, etc.) have long been utilized by park agencies to share safety, regulatory, and interpretive information with park visitors. While the study of these communications is an underserved field of research, even less attention has been paid specifically to the utility of social media communications at delivering park agency messaging to visitors, especially in the context of addressing visitor behaviour issues using social media communications. This study will contribute to this identified research gap by exploring the experiences of both park visitors and park managers with respect to the effectiveness of social media communications for park visitor behaviour management. To do so, this study applied interpretive description methodology (Thorne, 2016) to support semi-structured interviews with park visitors and individuals who work for park agencies in Ontario in park management roles. 17 participants participated in the research project throughout the course of the data collection process. Conversations with participants revealed that the utility of social media communications for visitor behaviour management varies widely depending on the sophistication of the park agency’s social media strategy. Park visitors often expressed a desire for more specific, authentic, and discussion-oriented communications, while park managers frequently expressed a need to improve and increase the resources and logistics dedicated to social media communications to meet park visitor expectations

On designing an algorithmically enhanced NHS: towards a conceptual model for the successful implementation of algorithmic clinical decision support software in the National Health Service

Established in 1948, the National Health Service (NHS) has lasted 75 years. It is, however, under considerable strain: facing chronic staff shortages; record numbers of emergency attendances; an ambulance wait-time crisis; and more. Increasingly, policymakers are of the view that the solution to these problems is to rely more heavily on one of the NHS’s greatest resources: its data. It is hoped that by combining the NHS’s data riches with the latest techniques in artificial intelligence (AI), that the means to make the NHS more effective, more efficient, and more consistent, can be identified and acted upon via the implementation of Algorithmic Clinical Decision Support Software (ACDSS). Yet, getting this implementation right will be both technically and ethically difficult. It will require a careful re-design of the NHS’s information infrastructure to ensure the implementation of ACDSS results in intended positive emergence (benefits), and not unintended negative emergence (harms and risks). This then is the purpose of my thesis. I seek to help policymakers with this re-design process by answering the research question ‘What are the information infrastructure requirements for the successful implementation of ACDSS in the NHS?’. I adopt a mixed-methods, theory-informed, and interpretive approach, and weave the results into a narrative policy synthesis. I start with an analysis of why current attempts to implement ACDSS into the NHS’s information infrastructure are failing and what needs to change to increase the chances of success; anticipate what might happen if these changes are not made; identify the exact requirements for bringing forth the changes; explain why the likelihood of these requirements being met by current policy is limited; and conclude by explaining how the likelihood of policy meeting the identified requirements can be increased by designing the ACDSS’s supporting information infrastructure around the core concepts of ‘utility, usability, efficacy, and trustworthiness’

Examining social media live stream’s influence on the consumer decision-making: a thematic analysis

oai:repository.uel.ac.uk:8x4q4Social media live streaming, in the form of live video and user stories, is widely used by influencers, organisations and individuals to connect with their audiences. Its popularity is well-established in a range of theoretical and managerial contexts. However, there is a lack of scholarship on the role of this phenomenon on consumer decision-making. Filling this gap in the research is essential due to the importance of consumer decision-making in marketing and brand strategy development in organisations. Therefore, the purpose of this paper is to explore and outline the nature of the influence of live stream on the consumer decision-making. The study was part of a 12-month Netnography consisting of participant observation and social media monitoring of brand pages and branded hashtags on social media platforms, Facebook, YouTube, Twitter and Instagram. A thematic analysis revealed five main themes and a conceptual model is proposed which outlines the social media live stream’s influence on consumer decision-making at each stage

Examining social media live stream’s influence on the consumer decision-making:a thematic analysis

Social media live streaming, in the form of live video and user stories, is widely used by influencers, organisations and individuals to connect with their audiences. Its popularity is well-established in a range of theoretical and managerial contexts. However, there is a lack of scholarship on the role of this phenomenon on consumer decision-making. Filling this gap in the research is essential due to the importance of consumer decision-making in marketing and brand strategy development in organisations. Therefore, the purpose of this paper is to explore and outline the nature of the influence of live stream on the consumer decision-making. The study was part of a 12-month Netnography consisting of participant observation and social media monitoring of brand pages and branded hashtags on social media platforms, Facebook, YouTube, Twitter and Instagram. A thematic analysis revealed five main themes and a conceptual model is proposed which outlines the social media live stream’s influence on consumer decision-making at each stage