The transition of Large Language Models (LLMs) from exploratory tools to active "silicon subjects" in social science lacks extensive validation of operational validity. This study introduces Conditioned Comment Prediction (CCP), a task in which a model predicts how a user would comment on a given stimulus by comparing generated outputs with authentic digital traces. This framework enables a rigorous evaluation of current LLM capabilities with respect to the simulation of social media user behavior. We evaluated open-weight 8B models (Llama3.1, Qwen3, Ministral) in English, German, and Luxembourgish language scenarios. By systematically comparing prompting strategies (explicit vs. implicit) and the impact of Supervised Fine-Tuning (SFT), we identify a critical form vs. content decoupling in low-resource settings: while SFT aligns the surface structure of the text output (length and syntax), it degrades semantic grounding. Furthermore, we demonstrate that explicit conditioning (generated biographies) becomes redundant under fine-tuning, as models successfully perform latent inference directly from behavioral histories. Our findings challenge current "naive prompting" paradigms and offer operational guidelines prioritizing authentic behavioral traces over descriptive personas for high-fidelity simulation.
The objective of this article is to analyse selected topics included in the corporate social responsibility (CSR) reports of companies from three Visegrad Group countries: Czechia, Poland, and Slovakia. The study focuses on the emphasis that these companies place on the topics discussed and the extent to which they include them in their CSR reports to stakeholders. The study adopts a quantitative design, using an online questionnaire to explore CSR reporting in the Visegrad countries, with a sample size of 375 companies. It employs statistical tools like the Shapiro–Wilk normality test, the Kruskal-Wallis test, and the Bonferroni post hoc test to analyse data on CSR reporting across different company sizes and sectors. Despite potential methodological limitations and bias, the survey identifies differences in CSR reporting practices among companies in the three countries. The leader in CSR reporting in the region is Slovakia, which can serve as an example of good CSR reporting practices. Czechia shows moderate commitment to CSR reporting activities, while companies in Poland are the least engaged. The discrepancies are due to differences in regulations, levels of public awareness, and business priorities. The results of the study will be valuable to researchers, managers and policymakers in developing tools to support companies in introducing new reporting standards and providing information on actions taken during a crisis. The novelty of this article is the analysis, at the enterprise level, of the type of CSR activities of selected companies from Visegrad Group countries from the perspective of the anti-crisis measures they have taken. This research fills a gap in the literature and provides a basis for discussing the legitimacy of socially responsible activities in contexts extending beyond a single crisis.
There have been global regulatory debates and efforts aimed at holding digital platforms accountable for the public interest. Utilizing mixed methods of documentary research and expert interviews, this article examines how the Chinese digital giant Tencent leverages its adaptive capabilities for corporate social responsibility (CSR) initiatives in response to increasingly stringent regulation in China. Specifically, it explores Tencent’s organizational restructuring, including the establishment of the sustainable social value (SSV) division, as well as the accompanying corporate practices and discursive strategies aimed at enhancing its legitimacy. As an exemplar of the “institutional chameleon,” Tencent has deftly navigated regulatory waters through organizational metamorphosis. However, while Tencent’s enhanced CSR initiatives have certainly yielded some social benefits, the SSV initiatives are increasingly emerging as a new business frontier for the company, leveraging its vast infrastructural capacities to capitalize on the very social fabric it purports to support. This underscores the complexities and contradictions inherent in its CSR practices and the significance of the intrinsic logic of digital platforms as a modern business.
Social media platforms frequently impose restrictive policies to moderate user content, prompting the emergence of creative evasion language strategies. This paper presents a multi-agent framework based on Large Language Models (LLMs) to simulate the iterative evolution of language strategies under regulatory constraints. In this framework, participant agents, as social media users, continuously evolve their language expression, while supervisory agents emulate platform-level regulation by assessing policy violations. To achieve a more faithful simulation, we employ a dual design of language strategies (constraint and expression) to differentiate conflicting goals and utilize an LLM-driven GA (Genetic Algorithm) for the selection, mutation, and crossover of language strategies. The framework is evaluated using two distinct scenarios: an abstract password game and a realistic simulated illegal pet trade scenario. Experimental results demonstrate that as the number of dialogue rounds increases, both the number of uninterrupted dialogue turns and the accuracy of information transmission improve significantly. Furthermore, a user study with 40 participants validates the real-world relevance of the generated dialogues and strategies. Moreover, ablation studies validate the importance of the GA, emphasizing its contribution to long-term adaptability and improved overall results.
Gaspard Abel, Argyris Kalogeratos, Jean-Pierre Nadal
et al.
The emergence of online social platforms, such as social networks and social media, has drastically affected the way people apprehend the information flows to which they are exposed. In such platforms, various information cascades spreading among users is the main force creating complex dynamics of opinion formation, each user being characterized by their own behavior adoption mechanism. Moreover, the spread of multiple pieces of information or beliefs in a networked population is rarely uncorrelated. In this paper, we introduce the Mixture of Interacting Cascades (MIC), a model of marked multidimensional Hawkes processes with the capacity to model jointly non-trivial interaction between cascades and users. We emphasize on the interplay between information cascades and user activity, and use a mixture of temporal point processes to build a coupled user/cascade point process model. Experiments on synthetic and real data highlight the benefits of this approach and demonstrate that MIC achieves superior performance to existing methods in modeling the spread of information cascades. Finally, we demonstrate how MIC can provide, through its learned parameters, insightful bi-layered visualizations of real social network activity data.
Misinformation is a growing concern in a decade involving critical global events. While social media regulation is mainly dedicated towards the detection and prevention of fake news and political misinformation, there is limited research about religious misinformation which has only been addressed through qualitative approaches. In this work, we study the spread of fabricated quotes (Hadith) that are claimed to belong to Prophet Muhammad (the prophet of Islam) as a case study demonstrating one of the most common religious misinformation forms on Arabic social media. We attempt through quantitative methods to understand the characteristics of social media users who interact with fabricated Hadith. We spotted users who frequently circulate fabricated Hadith and others who frequently debunk it to understand the main differences between the two groups. We used Logistic Regression to automatically predict their behaviors and analyzed its weights to gain insights about the characteristics and interests of each group. We find that both fabricated Hadith circulators and debunkers have generally a lot of ties to religious accounts. However, circulators are identified by many accounts that follow the Shia branch of Islam, Sunni Islamic public figures from the gulf countries, and many Sunni non-professional pages posting Islamic content. On the other hand, debunkers are identified by following academic Islamic scholars from multiple countries and by having more intellectual non-religious interests like charity, politics, and activism.
Business Process Visualisations (BPVs) have become indispensable tools for organisations seeking to enhance their operational efficiency, decision-making capabilities, and overall performance. The burgeoning interest in process modeling and tool development, coupled with the rise of data visualisation field, underscores the significant role of visual tools in leveraging human cognition. Unlike traditional models, data visualisation approaches graphics from a novel angle, emphasising the potency of visual representations. This review aims to integrate the domains of BPV and data visualisation to assess their combined influence on organisational effectiveness comprehensively. Through a meticulous analysis of existing literature, this study aims to amalgamate insights on BPVs impact from a data visualisation standpoint, advocating for a design philosophy that prioritises user engagement to bolster organisational outcomes. Additionally, our systematic review has unveiled promising avenues for future research, identifying underexplored variables that influence the efficacy of BPVs, thereby charting a path for forthcoming scholarly inquiries.
Distrust of public serving institutions and anti-establishment views are on the rise (especially in the U.S.). As people turn to social media for information, it is imperative to understand whether and how social media environments may be contributing to distrust of institutions. In social media, content creators, influencers, and other opinion leaders often position themselves as having expertise and authority on a range of topics from health to politics, and in many cases devalue and dismiss institutional expertise to build a following and increase their own visibility. However, the extent to which this content appears and whether such content increases engagement is unclear. This study analyzes the prevalence of anti-establishment sentiment (AES) on the social media platform TikTok. Despite its popularity as a source of information, TikTok remains relatively understudied and may provide important insights into how people form attitudes towards institutions. We employ a computational approach to label TikTok posts as containing AES or not across topical domains where content creators tend to frame themselves as experts: finance and wellness. As a comparison, we also consider the topic of conspiracy theories, where AES is expected to be common. We find that AES is most prevalent in conspiracy theory content, and relatively rare in content related to the other two topics. However, we find that engagement patterns with such content varies by area, and that there may be platform incentives for users to post content that expresses anti-establishment sentiment.
Purpose This paper aims to contribute to the scholarly debate, ongoing in this and other journals, on the justification and extent of artificial intelligence (AI)-related responsibilities of a variety of segments of society, such as governments and parliaments, scientists, corporations, media and AI users. Among these, business has received less attention, in both academic and political speech, hence this paper’s attempt to decant the content of a principle of corporate social responsibility related to AI. Design/methodology/approach This conceptual paper is built on two pillars. Placing the discussion in a framework of corporate social responsibility, this paper first argues that in the AI age, the list of corporate social responsibility (CSR) principles should be updated to include one relevant to AI development and deployment. Second, this study looks at the possible content of a new CSR principle. Findings Born from and still permeated by ethical principles, CSR principles evolve in time, reflecting contemporary societal priorities. If we define CSR as the integration of social concerns in corporate decision-making, then preserving the relevance of the human in the age of AI should qualify as a CSR principle. Like other CSR principles (anticorruption, transparency, community engagement, etc.), this would start as voluntary, but could harden in time, if society deems it necessary. Human relevance is more appropriate than human centrality as a CSR principle, despite the latter being referred to as a desideratum in numerous studies, policies and political statements on AI governance. Originality/value To the best of the author’s knowledge, this study is the first to demonstrate that in the age of AI, the list of recognized CSR principle should be updated to include an AI-related one. Introducing human relevance, as opposed to human centrality, as the content of such principle is also highly original, challenging current assumptions.
ABSTRACT This paper aimed to assess the impact of the changing business cycles on the CSR–Financial Performance relation of Indian firms. For this purpose, a panel data set of 70 Indian firms listed in NIFTY‐100 for a period of 10 years, that is, 2010–2019, was employed. CSR data for this study was collected from the published reports of the firms under study. The electronic database “Capitaline” was used as the data source for the financial variables. The paper used panel data modeling to study the effect of CSR on financial performance. Also, robustness analysis was conducted to check the results across alternate specifications. The results revealed that CSR has a significant negative impact on financial performance in the expansion phases. In contrast, no significant impact was observed in the recession phases of business cycles.
Astuti Rini Juni, Maryati Tri, Nurmalasari Aldanti Aulia
et al.
This study aims to examine the direct and indirect effect of servant leadership on Corporate Social Responsibility (CSR) and the effect of servant leadership on Innovativeness. This study is a survey study with 210 respondents of retail business employees in Yogyakarta, Indonesia. This research is classified as a basic research category with empirical evidence that is cross-sectional, and studies the development of interactions between leaders and followers. This type of research data is primary data using questionnaires. The sampling technique in this study uses purposive sampling, employees have worked for at least 1 year. Hypothesis testing in this study uses Path Analysis. The results of this study are that part of the hypothesis is accepted and partly not accepted. The results of the studies received are as follows: (1) Servant Leadership had a positive effect on CSR, (2) Servant Leadership had a positive effect on Innovativeness (3) Servant Leadership had a positive effect on Organizational Culture (4) Organizational culture mediated the effect of servant leadership on CSR, (5) CSR mediated the effect of servant leadership on Innovativeness. Meanwhile, research results that are not accepted or have no effect are as follows: Organizational Culture do not effect on CSR and CSR do not effect on Innovativeness.
This book comparatively analyzes various forms of populism in countries with democratic political systems and regimes. In various chapters, the authors draw attention to the common elements of populism that have already emerged: the desire for political representation, a charismatic leader, a nationalist idealization of the historical role of ‘the people’, criticism of the EU, the Council of Europe, the OSCE and international law. In this book, various authors point out that populist phenomena are used to destroy both the tools and the rules and culture of democracy. Most populist political parties gain widespread acceptance among young people because of their extreme views and statements, thereby calling for the abandonment of democratic principles, that is, the political order and the rule of law. In this book, the authors use an interdisciplinary approach to highlight the importance of political and social accountability and responsibility, examining the major challenges facing current and future corporate leaders. In its various chapters, the authors propose counter-populist approaches for effectively measuring political and socially responsible action and accountability. In this context, the authors offer tools to combat the causes of populism in both the political and social spheres, as well as in business.
Political science (General), Political institutions and public administration (General)
Ismail Hossain, Sai Puppala, Md Jahangir Alam
et al.
User activities can influence their subsequent interactions with a post, generating interest in the user. Typically, users interact with posts from friends by commenting and using reaction emojis, reflecting their level of interest on social media such as Facebook, Twitter, and Reddit. Our objective is to analyze user history over time, including their posts and engagement on various topics. Additionally, we take into account the user's profile, seeking connections between their activities and social media platforms. By integrating user history, engagement, and persona, we aim to assess recommendation scores based on relevant item sharing by Hit Rate (HR) and the quality of the ranking system by Normalized Discounted Cumulative Gain (NDCG), where we achieve the highest for NeuMF 0.80 and 0.6 respectively. Our hybrid approach solves the cold-start problem when there is a new user, for new items cold-start problem will never occur, as we consider the post category values. To improve the performance of the model during cold-start we introduce collaborative filtering by looking for similar users and ranking the users based on the highest similarity scores.
Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Sina Abdidizaji
et al.
The rapid and widespread dissemination of misinformation through social networks is a growing concern in today's digital age. This study focused on modeling fake news diffusion, discovering the spreading dynamics, and designing control strategies. A common approach for modeling the misinformation dynamics is SIR-based models. Our approach is an extension of a model called 'SBFC' which is a SIR-based model. This model has three states, Susceptible, Believer, and Fact-Checker. The dynamics and transition between states are based on neighbors' beliefs, hoax credibility, spreading rate, probability of verifying the news, and probability of forgetting the current state. Our contribution is to push this model to real social networks by considering different classes of agents with their characteristics. We proposed two main strategies for confronting misinformation diffusion. First, we can educate a minor class, like scholars or influencers, to improve their ability to verify the news or remember their state longer. The second strategy is adding fact-checker bots to the network to spread the facts and influence their neighbors' states. Our result shows that both of these approaches can effectively control the misinformation spread.
Abstract Based on a total of 1,590 listed non-financial firms on the Taiwan Stock Exchange and the Taipei Exchanges covering the period of 2007 ~ 2020, this study examines whether a firm's capital structure is affected by its corporate social responsibility (CSR) performance. While existing research has explored the impact of a firm’s CSR performance on various financial and non-financial consequences, this study argues that firm engaging in CSR is putting greater emphasis on the financial and bankruptcy risks arising from the use of debt financing and to maintain firm’s sustainability, firm with better CSR performance tends to reduce the use of debt. Through descriptive statistics, correlation analysis and multiple regression estimation, principal outcome shows that firm with better CSR performance tends to use less debt financing and inter-temporally reduce the use of debt.
Social responsibility of business, Business ethics
A social network population engages in collective actions as a direct result of forming a particular opinion. The strategic interactions among the individuals acting independently and selfishly naturally portray a noncooperative game. Nash equilibrium allows for self-enforcing strategic interactions between selfish and self-interested individuals. This paper presents a differential game approach to the opinion formation problem in social networks to investigate the evolution of opinions as a result of a Nash equilibrium. The opinion of each individual is described by a differential equation, which is the continuous-time Hegselmann-Krause model for opinion dynamics with a time delay in input. The objective of each individual is to seek optimal strategies for her own opinion evolution by minimizing an individual cost function. Two differential game problems emerge, one for a population that is not stubborn and another for a population that is stubborn. The open-loop Nash equilibrium actions and their associated opinion trajectories are derived for both differential games using Pontryagin's principle. Additionally, the receding horizon control scheme is used to practice feedback strategies where the information flow is restricted by fixed and complete social graphs as well as the second neighborhood concept. The game strategies were executed on the well-known Zachary's Karate Club social network. The resulting opinion trajectories associated with the game strategies showed consensus, polarization, and disagreement in final opinions.