Expressions of doubt and trust in online user reviews

How do expressions of doubt affect trust in online reviews? Some previous studies find that people trust confident advisors more than doubtful advisors, whereas others find doubtful advisors are trusted more. We tested the effects of expressing doubt using Yelp data and in a controlled experiment: In Study 1, reviews from Yelp (N = 5.9 million) were coded using the Linguistic Inquiry Word Count (LIWC) software. Reviews with doubtful language were seen as more useful, and this result was robust when controlling for other psychological and linguistic variables. In Study 2, participants (N = 660) evaluated reviews with doubtful or confident conclusions; doubtful reviews were seen as more likely to be written by actual consumers. In both studies, the positive effects of doubt were stronger for positive (vs. negative) reviews, suggesting doubt mitigates concerns about fake positive reviews. The present study emphasizes the advantages of expressing doubt

The relative importance of joke and audience characteristics in eliciting amusement

The current work estimated the relative importance of joke and audience characteristics for the occurrence of amusement. Much psychological research has focused on stimulus characteristics when searching for sources of funniness. Some researchers have instead highlighted the importance of perceiver characteristics, such as dispositional cheerfulness. Across five preregistered studies (Ns = 118–54,905) with varied stimuli and perceiver samples (website visitors, students, Mechanical Turk and Prolific users), variance-decomposition analyses found that perceiver characteristics account for more variance in funniness ratings than stimulus characteristics. Thus, psychological theories focusing on between-persons differences have a relatively high potential for explaining and predicting humor appreciation (here, funniness ratings). Crucially, perceiver-by-stimulus interactions explained the largest amount of variance, highlighting the importance of fit between joke and audience characteristics when predicting amusement. Implications for humor-appreciation theories and applications are discussed

Solving ARC visual analogies with neural embeddings and vector arithmetic: A generalized method

Analogical reasoning derives information from known relations and generalizes this information to similar yet unfamiliar situations. One of the first generalized ways in which deep learning models were able to solve verbal analogies was through vector arithmetic of word embeddings, essentially relating words that were mapped to a vector space (e.g., king - man + woman = __?). In comparison, most attempts to solve visual analogies are still predominantly task-specific and less generalizable. This project focuses on visual analogical reasoning and applies the initial generalized mechanism used to solve verbal analogies to the visual realm. Taking the Abstraction and Reasoning Corpus (ARC) as an example to investigate visual analogy solving, we use a variational autoencoder (VAE) to transform ARC items into low-dimensional latent vectors, analogous to the word embeddings used in the verbal approaches. Through simple vector arithmetic, underlying rules of ARC items are discovered and used to solve them. Results indicate that the approach works well on simple items with fewer dimensions (i.e., few colors used, uniform shapes), similar input-to-output examples, and high reconstruction accuracy on the VAE. Predictions on more complex items showed stronger deviations from expected outputs, although, predictions still often approximated parts of the item's rule set. Error patterns indicated that the model works as intended. On the official ARC paradigm, the model achieved a score of 2% (cf. current world record is 21%) and on ConceptARC it scored 8.8%. Although the methodology proposed involves basic dimensionality reduction techniques and standard vector arithmetic, this approach demonstrates promising outcomes on ARC and can easily be generalized to other abstract visual reasoning tasks.Comment: Data and code can be found on https://github.com/foger3/ARC_DeepLearnin

The psychology of online activism and social movements:Relations between online and offline collective action

We review online activism and its relations with offline collective action. Social media facilitate online activism, particularly by documenting and collating individual experiences, community building, norm formation, and development of shared realities. In theory, online activism could hinder offline protests, but empirical evidence for slacktivism is mixed. In some contexts, online and offline action could be unrelated because people act differently online versus offline, or because people restrict their actions to one domain. However, most empirical evidence suggests that online and offline activism are positively related and intertwined (no digital dualism), because social media posts can mobilise others for offline protest. Notwithstanding this positive relationship, the internet also enhances the visibility of activism and therefore facilitates repression in repressive contexts

Would Chuck Norris certainly win the Hunger Games?: Simulating the result reliability of Battle Royale games through agent-based models

Background: The amount of random chance involved in multiplayer competitions varies depending on the structure of the competition. A hugely popular mode of competition is the Battle Royale, in which a group of participants semi-randomly encounters and battles each other until only one player is left. We utilized computer simulations to investigate how strongly the outcomes of different Battle Royale formats reflect the actual distribution of skill among the players. Further, we investigated which game features affect the congruency between skills and results. Method: We build agent-based models in NETLOGO to simulate the outcomes of different Battle Royale formats. Results: Our results consistently forwarded that outcomes from Battle Royale are only weakly aligned with actual player skills. Conclusion: Our findings suggest that many forms of Battle Royale involve substantially more luck than other sports or e-sports competitions. Further, game developers should note that introducing new game features can entail both higher and lower involvement of skill over luck, and that these features can be tuned to obtain a desired level of uncertainty