Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter's Trending Topics

In addition to more personalized content feeds, some leading social media platforms give a prominent role to content that is more widely popular. On Twitter, "trending topics" identify popular topics of conversation on the platform, thereby promoting popular content which users might not have otherwise seen through their network. Hence, "trending topics" potentially play important roles in influencing the topics users engage with on a particular day. Using two carefully constructed data sets from India and Turkey, we study the effects of a hashtag appearing on the trending topics page on the number of tweets produced with that hashtag. We specifically aim to answer the question: How many new tweeting using that hashtag appear because a hashtag is labeled as trending? We distinguish the effects of the trending topics page from network exposure and find there is a statistically significant, but modest, return to a hashtag being featured on trending topics. Analysis of the types of users impacted by trending topics shows that the feature helps less popular and new users to discover and spread content outside their network, which they otherwise might not have been able to do.Comment: Accepted at ICWSM 2023. Please cite the ICWSM version. You're the bes

The Mere Exposure Effect in the Domain of Haptics

Background: Zajonc showed that the attitude towards stimuli that one had been previously exposed to is more positive than towards novel stimuli. This mere exposure effect (MEE) has been tested extensively using various visual stimuli. Research on the MEE is sparse, however, for other sensory modalities. Methodology/Principal Findings: We used objects of two material categories (stone and wood) and two complexity levels (simple and complex) to test the influence of exposure frequency (F0 = novel stimuli, F2 = stimuli exposed twice, F10 = stimuli exposed ten times) under two sensory modalities (haptics only and haptics & vision). Effects of exposure frequency were found for high complex stimuli with significantly increasing liking from F0 to F2 and F10, but only for the stone category. Analysis of ‘‘Need for Touch’ ’ data showed the MEE in participants with high need for touch, which suggests different sensitivity or saturation levels of MEE. Conclusions/Significance: This different sensitivity or saturation levels might also reflect the effects of expertise on the haptic evaluation of objects. It seems that haptic and cross-modal MEEs are influenced by factors similar to those in the visual domain indicating a common cognitive basis

Assessing the Effects and Risks of Large Language Models in AI-Mediated Communication

198 pagesLarge language models like GPT-3 are increasingly becoming part of human communication. Through writing suggestions, grammatical assistance, and machine translation, the models enable people to communicate more efficiently. Yet, we have a limited understanding of how integrating them into communication will change culture and society. For example, a language model that preferably generates a particular view may influence people's opinions when integrated into widely used applications. This dissertation empirically demonstrates that embedding large language models into human communication poses systemic societal risks. In a series of experiments, I show that humans cannot detect language produced by GPT-3, that using large language models in communication may undermine interpersonal trust, and that interactions with opinionated language models change users' attitudes. I introduce the concept of AI-Mediated Communication–where AI technologies modify, augment, or generate what people say–to theorize how the use of large language models in communication presents a paradigm shift from previous forms of computer-mediated communication. I conclude by discussing how my findings highlight the need to manage the risks of AI technologies like large language models in ways that are more systematic, democratic, and empirically grounded

Human Heuristics for AI-Generated Language Are Flawed

Human communication is increasingly intermixed with language generated by AI. Across chat, email, and social media, AI systems produce smart replies, autocompletes, and translations. AI-generated language is often not identified as such but poses as human language, raising concerns about novel forms of deception and manipulation. Here, we study how humans discern whether one of the most personal and consequential forms of language - a self-presentation - was generated by AI. In six experiments, participants (N = 4,600) tried to detect self-presentations generated by state-of-the-art language models. Across professional, hospitality, and dating settings, we find that humans are unable to detect AI-generated self-presentations. Our findings show that human judgments of AI-generated language are handicapped by intuitive but flawed heuristics such as associating first-person pronouns, spontaneous wording, or family topics with humanity. We demonstrate that these heuristics make human judgment of generated language predictable and manipulable, allowing AI systems to produce language perceived as more human than human. We discuss solutions, such as AI accents, to reduce the deceptive potential of generated language, limiting the subversion of human intuition

A Model for Haptic Aesthetic Processing and Its Implications for Design

Research in aesthetics typically focuses on static stimuli or stimulus properties from the visual domain leaving unanswered a great many questions on haptic aesthetics. This paper aims to give a short impression of the relevance of aesthetics for design and everyday-life decisions, then focuses on phenomena concerning haptic aesthetics in particular, for instance, top–down processes and mere exposure effects. Based on empirical findings and theoretical considerations with regard to haptic research, the paper develops a functional model of haptic aesthetics, which is explained step by step. This model assumes a continuous increase of elaborative processing through three subsequent processing stages beginning with low-level perceptual analyses that encompass an initial, unspecific exploration of the haptic material. After a subsequent, more elaborate, and specific perceptual assessment of global haptic aspects, the described process enters into deeper cognitive and emotional evaluations involving individual knowledge on the now specified haptic material. The paper closes with an applied view on design issues to explicate the importance of integrating haptic aesthetics into corresponding approaches

Positive fEMG Patterns with Ambiguity in Paintings

Whereas ambiguity in everyday life is often negatively evaluated, it is considered key in art appreciation. In a facial EMG study, we tested whether the positive role of visual ambiguity in paintings is reflected in a continuous affective evaluation on a subtle level. We presented ambiguous (disfluent) and non-ambiguous (fluent) versions of Magritte paintings and found that M. Zygomaticus major activation was higher and M. corrugator supercilii activation was lower for ambiguous than for non-ambiguous versions. Our findings reflect a positive continuous affective evaluation to visual ambiguity in paintings over the 5 s presentation time. We claim that this finding is indirect evidence for the hypothesis that visual stimuli classified as art, evoke a safe state for indulging into experiencing ambiguity, challenging the notion that processing fluency is generally related to positive affect

Comparison of analysis by stimuli: effects of pre-evaluation exposure frequency (F0, F2, F10) on liking in Experiment 1 (left) and in Experiment 2 (right) in the category stone.

<p>Comparison of analysis by stimuli: effects of pre-evaluation exposure frequency (F0, F2, F10) on liking in Experiment 1 (left) and in Experiment 2 (right) in the category stone.</p

Examples of objects used in the Experiments. Note: The white base was added only for the photographic documentation.

<p>Examples of objects used in the Experiments. Note: The white base was added only for the photographic documentation.</p

Image Ambiguity and Fluency

<div><p>Ambiguity is often associated with negative affective responses, and enjoying ambiguity seems restricted to only a few situations, such as experiencing art. Nevertheless, theories of judgment formation, especially the “processing fluency account”, suggest that easy-to-process (non-ambiguous) stimuli are processed faster and are therefore preferred to (ambiguous) stimuli, which are hard to process. In a series of six experiments, we investigated these contrasting approaches by manipulating fluency (presentation duration: 10ms, 50ms, 100ms, 500ms, 1000ms) and testing effects of ambiguity (ambiguous versus non-ambiguous pictures of paintings) on classification performance (Part A; speed and accuracy) and aesthetic appreciation (Part B; liking and interest). As indicated by signal detection analyses, classification accuracy increased with presentation duration (Exp. 1a), but we found no effects of ambiguity on classification speed (Exp. 1b). Fifty percent of the participants were able to successfully classify ambiguous content at a presentation duration of 100 ms, and at 500ms even 75% performed above chance level. Ambiguous artworks were found more interesting (in conditions 50ms to 1000ms) and were preferred over non-ambiguous stimuli at 500ms and 1000ms (Exp. 2a - 2c, 3). Importantly, ambiguous images were nonetheless rated significantly harder to process as non-ambiguous images. These results suggest that ambiguity is an essential ingredient in art appreciation even though or maybe <i>because</i> it is harder to process.</p> </div