Related papers: Credibility Analysis in Social Big Data
User trust in Artificial Intelligence (AI) enabled systems has been increasingly recognized and proven as a key element to fostering adoption. It has been suggested that AI-enabled systems must go beyond technical-centric approaches and…
Defining trust is an important endeavor given its applicability to assessing public mood to much of the innovation in the newly formed autonomous industry, such as artificial intelligence (AI),medical bots, drones, autonomous vehicles, and…
Understanding the sociodemographic composition of online platforms is essential for accurately interpreting digital behavior and its societal implications. Yet, current methods often lack the transparency and reliability required, risking…
There are mostly two approaches to tackle trust management worldwide Strong and crisp and Soft and Social. We analyze the impact of integrated trust mechanism in three different e-commerce services. The trust aspect is a dormant element…
Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applied to a large and statistically significant portion of the…
Social Media are evolving as a pervasive source of news able to reach a larger audience through their spreading power. The main drawback is given by the presence of malicious accounts, known as social bots, which are often used to diffuse…
Subjective Well-being(SWB), which refers to how people experience the quality of their lives, is of great use to public policy-makers as well as economic, sociological research, etc. Traditionally, the measurement of SWB relies on…
Susceptibility to misinformation describes the degree of belief in unverifiable claims, a latent aspect of individuals' mental processes that is not observable. Existing susceptibility studies heavily rely on self-reported beliefs, which…
While deep learning models have greatly improved the performance of most artificial intelligence tasks, they are often criticized to be untrustworthy due to the black-box problem. Consequently, many works have been proposed to study the…
One of the most significant problems of Big Data is to extract knowledge through the huge amount of data. The usefulness of the extracted information depends strongly on data quality. In addition to the importance, data quality has recently…
Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision making and communication of the latest guidelines pertaining to the treatment and management of the disorder…
Maintaining high quality content is one of the foremost objectives of any web-based collaborative service that depends on a large number of users. In such systems, it is nearly impossible for automated scripts to judge semantics as it is to…
Trust evaluation is an important topic in both research and applications in sociable environments. This paper presents a model for trust evaluation between agents by the combination of direct trust, indirect trust through neighbouring links…
One of the goals of every business enterprise is to increase customer loyalty. The degree of customer loyalty is called customer quality which its forecasting will affect strategic marketing practices. The purpose of this study is to…
The digital revolution has led to the digitization of human behavior, creating unprecedented opportunities to understand observable actions on an unmatched scale. Emerging phenomena such as crowdfunding and crowdsourcing have further…
Crypto Key Opinion Leaders (KOLs) shape Web3 narratives and retail investment behaviour. In volatile, high-risk markets, their credibility becomes a key determinant of their influence on followers. Yet prior research has focused on…
While new technologies are expected to revolutionise and become game-changers in improving the efficiencies and practises of our daily lives, it is also critical to investigate and understand the barriers and opportunities faced by their…
Data credibility is a crucial issue in mobile crowd sensing (MCS) and, more generally, people-centric Internet of Things (IoT). Prior work takes approaches such as incentive mechanism design and data mining to address this issue, while…
In the age of social media and generative AI, the ability to automatically assess the credibility of online content has become increasingly critical, complementing traditional approaches to false information detection. Credibility…
Social media datasets are essential for research on a variety of topics, such as disinformation, influence operations, hate speech detection, or influencer marketing practices. However, access to social media datasets is often constrained…