arXiv subjects

Taha Yasseri

Publications and source records attributed to Taha Yasseri.

At least 37 records · Page 2Linked to original sources

arXiv2024

AI-enhanced Collective Intelligence

Current societal challenges exceed the capacity of humans operating either alone or collectively. As AI evolves, its role within human collectives will vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, together, can surpass the collective intelligence of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from complex network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising cognition, physical, and information layers. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. We explore how agents' diversity and interactions influence the system's collective intelligence and analyze real-world instances of AI-enhanced collective intelligence. We conclude by considering potential challenges and future developments in this field.

cs.CY↗

arXiv2024

Individual differences in knowledge network navigation

With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants' performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation.

physics.soc-ph↗

arXiv2023

Terrorist attacks sharpen the binary perception of "Us" vs. "Them"

Terrorist attacks not only harm citizens but also shift their attention, which has long-lasting impacts on public opinion and government policies. Yet measuring the changes in public attention beyond media coverage has been methodologically challenging. Here we approach this problem by starting from Wikipedia's répertoire of 5.8 million articles and a sample of 15 recent terrorist attacks. We deploy a complex exclusion procedure to identify topics and themes that consistently received a significant increase in attention due to these incidents. Examining their contents reveals a clear picture: terrorist attacks foster establishing a sharp boundary between "Us" (the target society) and "Them" (the terrorist as the enemy). In the midst of this, one seeks to construct identities of both sides. This triggers curiosity to learn more about "Them" and soul-search for a clearer understanding of "Us". This systematic analysis of public reactions to disruptive events could help mitigate their societal consequences.

physics.soc-ph↗

arXiv2023

Using word embeddings to analyse audience effects and individual differences in parenting Subreddits

Human beings adapt their language to the audience they interact with. To study the impact of audience and gender in a natural setting, we choose a domain where gender plays a particularly salient role: parenting. We collect posts from the three popular parenting Subreddits (i.e., topical communities on Reddit) r/Daddit, r/Mommit, and r/Parenting. These three Subreddits gather different audiences, respectively, self-identifying as fathers and mothers (ostensibly single-gender), and parents (explicitly mixed-gender). By selecting a sample of users who have published on both a single-gender and a mixed-gender Subreddit, we are able to explore both audience and gender effects. We analyse posts with word embeddings by adding the username as a token in the corpus. This way, we are able to compare user-tokens to word-tokens and measure their similarity. We also investigate individual differences in this context by comparing users who exhibit significant changes in their behaviour (high self-monitors) with those who show less variation (low self-monitors). Results show that r/Parenting users generally discuss a great diversity of topics while fathers focus more on advising others on educational and family matters. Mothers in r/Mommit distinguish themselves from other groups by primarily discussing topics such as medical care, sleep and potty training, and food. Both mothers and fathers celebrate parenting events and describe or comment on the physical appearance of their children with a single-gender audience. In terms of individual differences, we find that, especially on r/Parenting, high self-monitors tend to conform more to the norms of the Subreddit by discussing more of the topics associated with the Subreddit. In conclusion, this study shows how mothers and fathers express different concerns and change their behaviour for different group-based audiences.

cs.SI↗

arXiv2023

Between News and History: Identifying Networked Topics of Collective Attention on Wikipedia

The digital information landscape has introduced a new dimension to understanding how we collectively react to new information and preserve it at the societal level. This, together with the emergence of platforms such as Wikipedia, has challenged traditional views on the relationship between current events and historical accounts of events, with an ever-shrinking divide between "news" and "history". Wikipedia's place as the Internet's primary reference work thus poses the question of how it represents both traditional encyclopaedic knowledge and evolving important news stories. In other words, how is information on and attention towards current events integrated into the existing topical structures of Wikipedia? To address this we develop a temporal community detection approach towards topic detection that takes into account both short term dynamics of attention as well as long term article network structures. We apply this method to a dataset of one year of current events on Wikipedia to identify clusters distinct from those that would be found solely from page view time series correlations or static network structure. We are able to resolve the topics that more strongly reflect unfolding current events vs more established knowledge by the relative importance of collective attention dynamics vs link structures. We also offer important developments by identifying and describing the emergent topics on Wikipedia. This work provides a means of distinguishing how these information and attention clusters are related to Wikipedia's twin faces of encyclopaedic knowledge and current events -- crucial to understanding the production and consumption of knowledge in the digital age.

cs.CY↗

arXiv2023

The cost of coordination can exceed the benefit of collaboration in performing complex tasks

Humans and other intelligent agents often rely on collective decision making based on an intuition that groups outperform individuals. However, at present, we lack a complete theoretical understanding of when groups perform better. Here we examine performance in collective decision-making in the context of a real-world citizen science task environment in which individuals with manipulated differences in task-relevant training collaborated. We find 1) dyads gradually improve in performance but do not experience a collective benefit compared to individuals in most situations; 2) the cost of coordination to efficiency and speed that results when switching to a dyadic context after training individually is consistently larger than the leverage of having a partner, even if they are expertly trained in that task; and 3) on the most complex tasks having an additional expert in the dyad who is adequately trained improves accuracy. These findings highlight that the extent of training received by an individual, the complexity of the task at hand, and the desired performance indicator are all critical factors that need to be accounted for when weighing up the benefits of collective decision-making.

cs.SI↗

arXiv2023

Rapid rise and decay in petition signing

Contemporary collective action, much of which involves social media and other Internet-based platforms, leaves a digital imprint which may be harvested to better understand the dynamics of mobilization. Petition signing is an example of collective action which has gained in popularity with rising use of social media and provides such data for the whole population of petition signatories for a given platform. This paper tracks the growth curves of all 20,000 petitions to the UK government petitions website (http://epetitions.direct.gov.uk) and 1,800 petitions to the US White House site (https://petitions.whitehouse.gov), analyzing the rate of growth and outreach mechanism. Previous research has suggested the importance of the first day to the ultimate success of a petition, but has not examined early growth within that day, made possible here through hourly resolution in the data. The analysis shows that the vast majority of petitions do not achieve any measure of success; over 99 percent fail to get the 10,000 signatures required for an official response and only 0.1 percent attain the 100,000 required for a parliamentary debate (0.7 percent in the US). We analyze the data through a multiplicative process model framework to explain the heterogeneous growth of signatures at the population level. We define and measure an average outreach factor for petitions and show that it decays very fast (reducing to 0.1 pervent after 10 hours in the UK and 30 hours in the US). After a day or two, a petition's fate is virtually set. The findings challenge conventional analyses of collective action from economics and political science, where the production function has been assumed to follow an S-shaped curve.

physics.soc-ph↗

arXiv2022

Can crowdsourcing rescue the social marketplace of ideas?

Facebook and Twitter recently announced community-based review platforms to address misinformation. We provide an overview of the potential affordances of such community-based approaches to content moderation based on past research and preliminary analysis of Twitter's Birdwatch data. While our analysis generally supports a community-based approach to content moderation, it also warns against potential pitfalls, particularly when the implementation of the new infrastructure focuses on crowd-based "validation" rather than "collaboration." We call for multidisciplinary research utilizing methods from complex systems studies, behavioural sociology, and computational social science to advance the research on crowd-based content moderation.

cs.SI↗

arXiv2022

Football is becoming more predictable; Network analysis of 88 thousands matches in 11 major leagues

In recent years excessive monetization of football and professionalism among the players has been argued to have affected the quality of the match in different ways. On the one hand, playing football has become a high-income profession and the players are highly motivated; on the other hand, stronger teams have higher incomes and therefore afford better players leading to an even stronger appearance in tournaments that can make the game more imbalanced and hence predictable. To quantify and document this observation, in this work we take a minimalist network science approach to measure the predictability of football over 26 years in major European leagues. We show that over time, the games in major leagues have indeed become more predictable. We provide further support for this observation by showing that inequality between teams has increased and the home-field advantage has been vanishing ubiquitously. We do not include any direct analysis on the effects of monetization on football's predictability or therefore, lack of excitement, however, we propose several hypotheses which could be tested in future analyses.

physics.soc-ph↗

arXiv2022

Collective Memory in the Digital Age

The digital transformation of our societies and in particular information and communication technologies have revolutionized how we generate, communicate, and acquire information. Collective memory as a core and unifying force in our societies has not been an exception among many societal concepts which have been revolutionized through digital transformation. In this chapter, we have distinguished between "the digitalized collective memory" and "collective memory in the digital age". In addition to discussing these two main concepts, we discuss how digital tools and trace data can open doorways into the study of collective memory that is formed inside and outside of the digital space.

cs.CY↗

arXiv2022

What drives passion? An empirical examination on the impact of personality trait interactions and job environments on work passion

Passionate employees are essential for organisational success as they foster higher performance and exhibit lower turnover or absenteeism. While a large body of research has investigated the consequences of passion, we know only little about its antecedents. Integrating trait interaction theory with trait activation theory, this paper examines how personality traits, i.e. conscientiousness, agreeableness, and neuroticism impact passion at work across different job situations. Passion has been conceptualized as a two-dimensional construct, consisting of harmonious work passion (HWP) and obsessive work passion (OWP). Our study is based on a sample of N = 824 participants from the myPersonality project. We find a positive relationship between neuroticism and OWP in enterprising environments. Further, we find a three-way interaction between conscientiousness, agreeableness, and enterprising environment in predicting OWP. Our findings imply that the impact of personality configurations on different forms of passion is contingent on the job environment. Moreover, in line with self-regulation theory, the results reveal agreeableness as a "cool influencer" and neuroticism as a "hot influencer" of the relationship between conscientiousness and work passion. We derive practical implications for organisations on how to foster work passion, particularly HWP, in organisations.

cs.SI↗

arXiv2021

Positive algorithmic bias cannot stop fragmentation in homophilic networks

Fragmentation, echo chambers, and their amelioration in social networks have been a growing concern in the academic and non-academic world. This paper shows how, under the assumption of homophily, echo chambers and fragmentation are system-immanent phenomena of highly flexible social networks, even under ideal conditions for heterogeneity. We achieve this by finding an analytical, network-based solution to the Schelling model and by proving that weak ties do not hinder the process. Furthermore, we derive that no level of positive algorithmic bias in the form of rewiring is capable of preventing fragmentation and its effect on reducing the fragmentation speed is negligible.

cs.SI↗

arXiv2021

Dissent and Rebellion in the House of Commons: A Social Network Analysis of Brexit-Related Divisions in the 57$^{ th}$ Parliament

The British party system is known for its discipline and cohesion, but it remains wedged on one issue: European integration. We offer a methodology using social network analysis that considers the individual interactions of MPs in the voting process. Using public Parliamentary records, we scraped votes of individual MPs in the 57th parliament (June 2017 to April 2019), computed pairwise similarity scores and calculated rebellion metrics based on eigenvector centralities. Comparing the networks of Brexit- and non-Brexit divisions, our methodology was able to detect a significant difference in eurosceptic behaviour for the former, and using a rebellion metric we predicted how MPs would vote in a forthcoming Brexit deal with over 90% accuracy.

physics.soc-ph↗

arXiv2021

Selling sex: what determines rates and popularity? An analysis of 11,500 online profiles

Sex work, or the exchange of sexual services for money or goods, is ubiquitous across eras and cultures. However, the practice of selling sex is often hidden due to stigma and the varying legal status of sex work. Online platforms that sex workers use to advertise services have become an increasingly important means of studying a market that is largely hidden. Although prior literature has primarily shed light on sex work from a public health or policy perspective (focusing largely on female sex workers), there are few studies that empirically research patterns of service provision in online sex work. This study investigated the determinants of pricing and popularity in the market for commercial sexual services online by using data from the largest UK network of online sexual services, a platform that is the industry-standard for sex workers. While the size of these influences varies across genders, nationality, age and the services provided are shown to be primary drivers of rates and popularity in sex work.

cs.CY↗

arXiv2021

The Kaleidoscope of Privacy: Differences across French, German, UK, and US GDPR Media Discourse

Conceptions of privacy differ by culture. In the Internet age, digital tools continuously challenge the way users, technologists, and governments define, value, and protect privacy. National and supranational entities attempt to regulate privacy and protect data managed online. The European Union passed the General Data Protection Regulation (GDPR), which took effect on 25 May 2018. The research presented here draws on two years of media reporting on GDPR from French, German, UK, and US sources. We use the unsupervised machine learning method of topic modelling to compare the thematic structure of the news articles across time and geographic regions. Our work emphasises the relevance of regional differences regarding valuations of privacy and potential obstacles to the implementation of unilateral data protection regulation such as GDPR. We find that the topics and trends over time in GDPR media coverage of the four countries reflect the differences found across their traditional privacy cultures.

cs.CY↗

arXiv2021

Islamophobes are not all the same! A study of far right actors on Twitter

Far-right actors are often purveyors of Islamophobic hate speech online, using social media to spread divisive and prejudiced messages which can stir up intergroup tensions and conflict. Hateful content can inflict harm on targeted victims, create a sense of fear amongst communities and stir up intergroup tensions and conflict. Accordingly, there is a pressing need to better understand at a granular level how Islamophobia manifests online and who produces it. We investigate the dynamics of Islamophobia amongst followers of a prominent UK far right political party on Twitter, the British National Party. Analysing a new data set of five million tweets, collected over a period of one year, using a machine learning classifier and latent Markov modelling, we identify seven types of Islamophobic far right actors, capturing qualitative, quantitative and temporal differences in their behaviour. Notably, we show that a small number of users are responsible for most of the Islamophobia that we observe. We then discuss the policy implications of this typology in the context of social media regulation.

cs.SI↗

arXiv2021

Gender Imbalance and Spatiotemporal Patterns of Contributions to Citizen Science Projects: the case of Zooniverse

Citizen Science is research undertaken by professional scientists and members of the public collaboratively. Despite numerous benefits of citizen science for both the advancement of science and the community of the citizen scientists, there is still no comprehensive knowledge of patterns of contributions, and the demography of contributors to citizen science projects. In this paper we provide a first overview of spatiotemporal and gender distribution of citizen science workforce by analyzing 54 million classifications contributed by more than 340 thousand citizen science volunteers from 198 countries to one of the largest citizen science platforms, Zooniverse. First we report on the uneven geographical distribution of the citizen scientist and model the variations among countries based on the socio-economic conditions as well as the level of research investment in each country. Analyzing the temporal features of contributions, we report on high "burstiness" of participation instances as well as the leisurely nature of participation suggested by the time of the day that the citizen scientists were the most active. Finally, we discuss the gender imbalance among citizen scientists (about 30% female) and compare it with other collaborative projects as well as the gender distribution in more formal scientific activities. Citizen science projects need further attention from outside of the academic community, and our findings can help attract the attention of public and private stakeholders, as well as to inform the design of the platforms and science policy making processes.

physics.soc-ph↗

arXiv2021

Credit Crunch: The Role of Household Lending Capacity in the Dutch Housing Boom and Bust 1995-2018

What causes house prices to rise and fall? Economists identify household access to credit as a crucial factor. "Loan-to-Value" and "Debt-to-GDP" ratios are the standard measures for credit access. However, these measures fail to explain the depth of the Dutch housing bust after the 2009 Financial Crisis. This work is the first to model household lending capacity based on the formulas that Dutch banks use in the mortgage application process. We compare the ability of regression models to forecast housing prices when different measures of credit access are utilised. We show that our measure of household lending capacity is a forward-looking, highly predictive variable that outperforms `Loan-to-Value' and debt ratios in forecasting the Dutch crisis. Sharp declines in lending capacity foreshadow the market deceleration.

stat.AP↗