Understanding Online Trust and Information Behavior Using Demographics and Human Values

Verma, Nitin; Fleischmann, Kenneth R.; Koltai, Kolina

doi:10.1007/978-3-030-15742-5_62

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…Only more recently, Human Values have also been explored in conjunction with other demographic features to understand how different individuals relate to misinformation. Verma et al (2019), for example, found connections between valuing security, and trust in mainstream media. To our knowledge, detecting values has not yet become a primary part of the misinformation detection or prioritisation process.…”

Section: Human Valuesmentioning

confidence: 99%

Understanding the Role of Human Values in the Spread of Misinformation

Farrell¹,

Piccolo²,

Perfumi³

et al. 2019

Proceedings of the Conference for Truth and Trust Online 2019

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Social media platforms are often implicated in the spread of misinformation for encouraging the behaviour of rapid-sharing without adequate mechanisms for verifying information. To counter this phenomena, much related research in computer science has been focusing on developing tools to detect misinformation, to rank fact-check-worthy claims, and to understand their spread patterns, while psychosocial approaches have been focused on understanding information literacy, ideology and partisanship. In this paper, we demonstrate through a survey of nearly 100 people that the Human Values could have a significant influence on the way people perceive and share information. We argue that integrating a valuesoriented perspective into computational approaches for handling misinformation could encourage misinformation prevention, and assist in predicting and ranking misinformation.

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Section: Human Valuesmentioning

confidence: 99%

Understanding the Role of Human Values in the Spread of Misinformation

Farrell¹,

Piccolo²,

Perfumi³

et al. 2019

Proceedings of the Conference for Truth and Trust Online 2019

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“…In addition, fake news can negatively impact a brand's image, making retaining and attracting new customers more challenging. The impact of fake news on consumers' brand trust and experiences occurs when the advertised products and services do meet their expectations or fulfill the promises [93,94]. For instance, when brands use inaccurate information to promote specific products, there might be discrepancies between the promised value and the actual value the customers get after using a product [95].…”

Section: The Impact Of Fake News On Brand Equity Consumer Trust and E...mentioning

confidence: 99%

Fake News in Marketing

Silva¹,

Rosário²,

Gestoso³

et al. 2023

Preprint

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Fake news was conventionally assumed to mean fabricated information published in newspapers and other mass media. It was mostly done to increase the paper's sales and was unlikely to have long-term impacts on society. Fake news in marketing concerns intentionally delivering false or misleading information regarding a product or service to influence consumer behavior. Despite the severity of these impacts, we noted that there is very little scientific research on fake news in marketing and consumer behavior. This systematic literature review (LRSB) aims to bridge this knowledge gap by searching and analysing relevant publications on "fake news in marketing" and synthesising data from 117 relevant studies, providing a framework for marketers and business leaders to reduce the spread and impact of online misinformation. The main highlights identify that the implementation and use of social media, shaping a presence on the internet, diffusion, and consumption of fake news have become a serious challenge and a dominant problem in the marketing sector, especially with the growth of digital marketing. Strategically, fake news spread can be categorized into various types, and the use of these tactics can produce short-term benefits such as increased engagement and instant sales, but they can also have severe long-term costs such as reputational damage, loss of revenues and market share, and discouraged investors and shareholders.

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“…Many people are aware of the fact that online content is filtered, sorted, and distributed according to user characteristics such as demographics and opinions [18]. The process of using ML to filter content can be opaque and flawed.…”

Section: Social Media and Ml-based Filteringmentioning

confidence: 99%

Perceived Social Media Bias, Social Identity Threat, and Conspiracy Theory Ideation During the COVID-19 Pandemic

Craig¹,

Sadovykh²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Social media organizations have an obligation to filter and sometimes exclude content, often based on machine learning algorithms. This has resulted in perceptions of bias in social media. When individuals perceive that a social media system is designed to exclude their point of view, they may experience a loss of self-worth, based on their excluded point of view. As a result, they may resist and avoid the technology that seems biased against them to prevent further loss of selfworth. They might also believe in conspiracies about why social media is marginalizing their point of view and find new self-worth as a conspiracy theorist. Data from 225 individuals who are interested in the risks associated with vaccines indicate that Perceived Bias presents a Social Identity Threat, which, in turn, is associated with Resistance to IT and Conspiracy Theorist Ideation.

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Understanding Online Trust and Information Behavior Using Demographics and Human Values

Cited by 6 publications

References 27 publications

Understanding the Role of Human Values in the Spread of Misinformation

Understanding the Role of Human Values in the Spread of Misinformation

Fake News in Marketing

Perceived Social Media Bias, Social Identity Threat, and Conspiracy Theory Ideation During the COVID-19 Pandemic

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