This article examines the evolution of peer review and the modern editorial processes of scholarly journals by analyzing a novel data set derived from the Royal Society’s archives and covering ...1865-1965, that is, the historical period in which refereeing (not yet known as peer review) became firmly established. Our analysis reveals how the Royal Society’s editorial processes coped with both an increasing reliance on refereeing and a growth in submissions, while maintaining collective responsibility and minimizing research waste. By engaging more of its fellows in editorial activity, the society was able to establish an equilibrium of number of submissions per reviewer that was relatively stable over time. Nevertheless, our analysis shows that the distribution of editorial work was significantly uneven. Our findings reveal interesting parallels with current concerns about the scale and distribution of peer review work and suggest the strategic importance of the management of the editorial process to achieve a creative mix of community commitment and professional responsibility that is essential in contemporary journals.
Persuasion techniques play a vital role in human communication, influencing various aspects of our lives. With the increasing prevalence of digital platforms, these techniques have permeated online ...spaces such as websites, mobile apps, games, and social media. This article presents a dataset collected via a survey, designed to gather information about individuals' demographics, personality traits, dysfunctional attitudes, and their responses to statements embedded with persuasion techniques. Core messages promoting paid news subscriptions, blood donations, and exercise serve as the focus, while definitions and examples of persuasive techniques are provided. By analyzing this comprehensive dataset, researchers could gain valuable insights into the influence and impact of persuasive communication strategies.
The present paper describes the design and evaluation of a videogame developed to support math education and overcome math anxiety (MA) at the primary school level. The game narrative is based on the ...history of math. The player travels back on time and meets on-player characters such as Pythagoras of Samos and Ada Lovelace, learning about how math was used during their times. The player is invited to play a minigame where the concepts shared by the characters are used as a strategy to win. The game’s evaluation consisted of a pre and post-testing study that measured students’ math performance and MA levels. The experiment also included a group interview to collect students’ perceptions about the game. The experiment lasted five weeks, and 88 students from three primary schools played the game on weekly sessions 45-60 minutes long. Statistical analysis suggested the game significantly improves students’ math performance. However, the results indicated that female students from one of the classrooms had higher MA levels after playing the game. In addition, qualitative data shows students had a high level of engagement with the gameplay.
Although subjective expressions and linguistic fluency have been shown as important factors in processing and interpreting textual facts, analyses of these traits in textual health information for ...different audiences are lacking. We analyzed the readability and linguistic psychological and emotional characteristics of different textual summary formats of Cochrane systematic reviews.
We performed a multitrait-multimethod cross-sectional study of Press releases available at Cochrane web site (n = 162) and corresponding Scientific abstracts (n = 158), Cochrane Clinical Answers (n = 35) and Plain language summaries in English (n = 156), French (n = 101), German (n = 41) and Croatian (n = 156). We used SMOG index to assess text readability of all text formats, and natural language processing tools (IBM Watson Tone Analyzer, Stanford NLP Sentiment Analysis and Linguistic Inquiry and Word Count) to examine the affective states and subjective information in texts of Scientific abstracts, Plain language summaries and Press releases.
All text formats had low readability, with SMOG index ranging from a median of 15.6 (95% confidence interval (CI) 15.3-15.9) for Scientific abstracts to 14.7 (95% CI 14.4-15.0) for Plain language summaries. In all text formats, "Sadness" was the most dominantly perceived emotional tone and the style of writing was perceived as "Analytical" and "Tentative". At the psychological level, all text formats exhibited the predominant "Openness" tone, and Press releases scored higher on the scales of "Conscientiousness", "Agreeableness" and "Emotional range". Press releases had significantly higher scores than Scientific abstracts and Plain language summaries on the dimensions of "Clout", and "Emotional tone".
Although the readability of Plain language summaries was higher than that of text formats targeting more expert audiences, the required literacy was much higher than the recommended US 6th grade level. The language of Press releases was generally more engaging than that of Scientific abstracts and Plain language summaries, which are written by the authors of systematic reviews. Preparation of textual summaries about health evidence for different audiences should take into account readers' subjective experiences to encourage cognitive processing and reaction to the provided information.
This article examines information-search heuristics and communication patterns in an online forum of investors during a period of market uncertainty. Global connections, real-time communication, and ...technological sophistication have created an unpredictable market environment. As such, investors try to deal with semantic, strategic, and operational uncertainty by following heuristics that reduce information redundancy. In this study, we have tried to find traces of cognitive communication heuristics in a large-scale data set including 8 years of online posts (2004–2012) for a forum of Italian investors. We identified various market volatility conditions on a daily basis to understand the influence of market uncertainty on cognitive and communication processes. We found that investors communicated more dynamically when the market was unstable, while they were more prone to anchor heuristic when market uncertainty was invariant. Furthermore, abnormal market trends triggered more availability-based communication patterns. We also found that expertise matters. This would suggest that online communities need intelligent, context-specific tools to support partner selection and stimulate nonredundant communication.
This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market ...trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks.
Introduction to the Special Issue on GaLA Conf 2021 De Rosa, Francesca; Baalsrud Hauge, Jannicke; Dondio, Pierpaolo ...
International journal of serious games,
09/2022, Letnik:
9, Številka:
3
Journal Article
Recenzirano
Odprti dostop
This is a short introduction pecial issue of the International Journal of Serious Games dedicated to the selected best papers of the 2021 edition of the Games and Learning (GALA) 2021 conference. The ...three selected papers have undergone a regular review process. Covered topics range from cooperative games to mixed reality, from digital companions to game co-design.
In this paper, we present the first meta-analysis of the efficacy of game-based interventions on reducing students’ levels of maths anxiety. After searching for randomised studies describing ...game-based interventions to reduce maths anxiety, 22 effect sizes with 913 participants described in 15 peer-review articles met the selection criteria. A random effects meta-analysis indicated a reduction of maths anxiety with a small effect size (mean effect size ES = −0.24, CI = − 0.47, −0.01), marginally significant at 0.05 level but not robust to a leave-one-out sensitivity analysis. Several factors moderated the results: non-digital games were more effective, while digital games had a negligible mean effect size of ES = −0.10, CI = − 0.24, 0.03. The effect size was also moderated by the total duration of the intervention, to the advantage of longer interventions, and by the type of gameplay: games had a greater effect on maths anxiety reduction when they promoted collaborative and social interactions. Such features were mainly present in non-digital games, while all bar one of the digital interventions used single-player games. The results obtained, which were particularly weak for digital games, indicated the need to develop and test games explicitly designed for maths-anxious students to increase the impact of game-based interventions. This will require investigation into the relationship between game features and maths anxiety through analysis of the behaviour of anxious and non-anxious students at play. Among the features that an anxiety-aware game could employ, we suggest collaborative gameplay, social interactions, adaptability, features promoting intrinsic motivation and embedding real-time measurements of maths anxiety in the game.
•There is weak and non-robust evidence that games can reduce math anxiety levels.•The effect is weaker for digital games, that showed a negligible effect, and stronger for non-digital games.•Collaborative games and longer interventions showed a stronger effect.•The results indicate the need to design games for math anxious students and analyse the game experience of players.
Purpose
Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) ...methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.
Design/methodology/approach
A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).
Findings
The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.
Research limitations/implications
In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.
Practical implications
The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.
Originality/value
This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.
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