Polls, clickbait, and commemorative $2 bills

Zeng, Eric; Wei, Miranda; Gregersen, Theo; Kohno, Tadayoshi; Roesner, Franziska

doi:10.1145/3487552.3487850

Cited by 18 publications

(15 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given the appeal of gossip and scandal, as illustrated by media outlets such as the National Enquirer or Access Hollywood on TV, advertisers can thus profit off sensationalized and potentially misinformed claims (e.g., Han et al, 2022). Another fundamental concern is that advertisements themselves contain misinformation (Baker, 2018;Braun & Loftus, 1998;Glaeser & Ujhelyi, 2010;Hattori & Higashida, 2014;Rao, 2022;Zeng et al, 2020Zeng et al, , 2021.…”

Section: Societal-level Effects Of Misinformationmentioning

confidence: 99%

(Why) Is Misinformation a Problem?

Adams

Osman

Bechlivanidis

et al. 2023

Perspect Psychol Sci

View full text Add to dashboard Cite

In the last decade there has been a proliferation of research on misinformation. One important aspect of this work that receives less attention than it should is exactly why misinformation is a problem. To adequately address this question, we must first look to its speculated causes and effects. We examined different disciplines (computer science, economics, history, information science, journalism, law, media, politics, philosophy, psychology, sociology) that investigate misinformation. The consensus view points to advancements in information technology (e.g., the Internet, social media) as a main cause of the proliferation and increasing impact of misinformation, with a variety of illustrations of the effects. We critically analyzed both issues. As to the effects, misbehaviors are not yet reliably demonstrated empirically to be the outcome of misinformation; correlation as causation may have a hand in that perception. As to the cause, advancements in information technologies enable, as well as reveal, multitudes of interactions that represent significant deviations from ground truths through people’s new way of knowing (intersubjectivity). This, we argue, is illusionary when understood in light of historical epistemology. Both doubts we raise are used to consider the cost to established norms of liberal democracy that come from efforts to target the problem of misinformation.

show abstract

Section: Societal-level Effects Of Misinformationmentioning

confidence: 99%

(Why) Is Misinformation a Problem?

Adams

Osman

Bechlivanidis

et al. 2023

Perspect Psychol Sci

View full text Add to dashboard Cite

show abstract

“…In considering these ambiguities, we will use the term 'dark patterns' in a broad sense, regardless of intention, to refer to design patterns that involve inducing certain emotions (e.g., guilt, fear, shame) or misleading mental models (e.g., a misconception of the system or their actions) to manipulate user behaviour towards certain ends-involving mechanisms or goals that the user is unaware of or did not consent to. 6 As noted earlier, the vast majority of literature on dark patterns has focused on how information is phrased or presented in graphic user interfaces (GUIs), most prominently cookie consent banners [5,6,19], ads on online platforms [30,66], and e-commerce websites [44,47,58]. Recently, a handful of papers have started considering dark patterns in the ways that other modalities interact with people, i.e., embodied interactions with robots [33,57], auditory interactions with voice user interfaces (VUIs) [52], and proxemic interactions with movable platforms [28].…”

Section: Distinguishing Nudges Dark and Anti-patternsmentioning

confidence: 99%

Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Socially

Alberts¹,

Kleek²

2023

Preprint

View full text Add to dashboard Cite

Fig. 1. Mock examples of notification messages with manipulative, rude, or tactless framing The Computers Are Social Actors paradigm suggests people exhibit social/anthropomorphic biases in their treatment of technology.Such insights have encouraged the design of interfaces that interact with users in more social (chatty or even friend-like) ways.However, in typical 'dark pattern' fashion, social-emotional responses to systems as (seemingly sentient) agents can be harnessed to manipulate user behaviour. An increasingly common example is app notifications that assume person-like tones to persuade or pressure users into compliance. Regardless of being manipulative, difficulties meeting contextual social expectations can make automated social acting seem rude, invasive, tactless, and even disrespectful-constituting 'social' anti-patterns. This paper explores ways to improve how automated systems treat people in interactions. We mixed four qualitative methods to elicit user experiences and preferences regarding how automated systems "talk" to/at them. We identify an emerging 'social' class of dark and anti-patterns, and propose guidelines for helping (social) interfaces treat users in more respectful, tactful, and autonomy-supportive ways.CCS Concepts: • Human-centered computing → Natural language interfaces; Empirical studies in interaction design; User centered design; Contextual design.

show abstract

“…They explained how fake news websites can proliferate by jumping from an ad network to another if they are blocked. In [71], authors studied problematic ads (e.g., clickbait, scams) and their prevalence across news and misinformation websites, as well as the ad platforms that serve them and found that similar ads are server in both categories. In [8], authors explored the advertising market and investigated both benign and unethical websites.…”

Section: Related Workmentioning

confidence: 99%

Leveraging Google’s Publisher-Specific IDs to Detect Website Administration

Papadogiannakis

Papadopoulos

Markatos

et al. 2022

Proceedings of the ACM Web Conference 2022

View full text Add to dashboard Cite

Digital advertising is the most popular way for content monetization on the Internet. Publishers spawn new websites, and older ones change hands with the sole purpose of monetizing user traffic. In this ever-evolving ecosystem, it is challenging to effectively answer questions such as: Which entities monetize what websites? What categories of websites does an average entity typically monetize on and how diverse are these websites? How has this website administration ecosystem changed across time?In this paper, we propose a novel, graph-based methodology to detect administration of websites on the Web, by exploiting the ad-related publisher-specific IDs. We apply our methodology across the top 1 million websites and study the characteristics of the created graphs of website administration. Our findings show that approximately 90% of the websites are associated each with a single publisher, and that small publishers tend to manage less popular websites. We perform a historical analysis of up to 8 million websites, and find a new, constantly rising number of (intermediary) publishers that control and monetize traffic from hundreds of websites, seeking a share of the ad-market pie. We also observe that over time, websites tend to move from big to smaller administrators. CCS CONCEPTS• Information systems → Web applications; Online advertising; Web mining.

show abstract

Polls, clickbait, and commemorative $2 bills

Cited by 18 publications

References 33 publications

(Why) Is Misinformation a Problem?

(Why) Is Misinformation a Problem?

Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Socially

Leveraging Google’s Publisher-Specific IDs to Detect Website Administration

Contact Info

Product

Resources

About