Policies for allocation of information in task-oriented groups: elitism and egalitarianism outperform welfarism

Communication or influence networks are probably the most controllable of all factors that are known to impact on the problem-solving capability of task-forces. In the case connections are costly, it is necessary to implement a policy to allocate them to the individuals. Here we use an agent-based model to study how distinct allocation policies affect the performance of a group of agents whose task is to find the global maxima of NK fitness landscapes. Agents cooperate by broadcasting messages informing on their fitness and use this information to imitate the fittest agent in their influence neighborhoods. The larger the influence neighborhood of an agent, the more links, and hence information, the agent receives. We find that the elitist policy in which agents with above-average fitness have their influence neighborhoods amplified, whereas agents with below-average fitness have theirs deflated, is optimal for smooth landscapes, provided the group size is not too small. For rugged landscapes, however, the elitist policy can perform very poorly for certain group sizes. In addition, we find that the egalitarian policy, in which the size of the influence neighborhood is the same for all agents, is optimal for both smooth and rugged landscapes in the case of small groups. The welfarist policy, in which the actions of the elitist policy are reversed, is always suboptimal, i.e., depending on the group size it is outperformed by either the elitist or the egalitarian policies

The impact of social media fitness influencer attractiveness on purchase intention of fitness items and self­-esteem as a moderator

The purpose of this thesis is to understand how social media fitness influencers’ attractiveness affects customers’ purchase intention for fitness items and if this effect differs considering customers self-­esteem. This thesis aims to explore how attractiveness, as one dimension of influencers’ credibility, might lead customers to purchase an endorsed item. Self­-esteem was included in this thesis as studies reveal that body image and exposition to attractiveness-­related content might influence self­-esteem and consequently decrease the persuasion effect. To better analyze the attractiveness of influencers and purchase intention, source­-credibility scale, purchase intention and Rosenberg self­-esteem scales were adapted and used. The data was collected through an online survey with 144 valid responses collected. The results of the present study did not find significant effects of social media fitness influencers’ attractiveness on consumers’ purchase intention for fitness items. Furthermore, results have revealed that consumer’s self­-esteem also does not moderate the effect of attractiveness on purchase intention. This thesis contributes to the academic community by providing a starting point for further research on the physical attributes of social media influencers that might have an impact on purchase intention in the emerging fitness market.O objectivo desta tese é compreender como a atractividade dos influenciadores de fitness dos meios de comunicação social afecta a intenção de compra de artigos de fitness e se este efeito difere considerando a auto­estima dos clientes. Esta tese visa explorar como a atractividade, como uma dimensão da credibilidade dos influenciadores, pode levar os clientes a comprar um artigo endossado. A auto­estima foi incluída nesta tese, uma vez que estudos revelam que a imagem corporal e a exposição a conteúdos relacionados com a atractividade podem influenciar a auto­estima e, consequentemente, diminuir o efeito de persuasão. Para melhor analis ar a atractividade dos influenciadores e a intenção de compra, foram adaptadas e utilizadas escalas de auto­estima Rosenberg e de intenção de compra. Os dados foram recolhidos através de um inquérito online, com 144 respostas válidas recolhidas. Os resultados do presente estudo não encontraram efeitos significativos da atractividade dos influenciadores das redes sociais na intenção de compra de artigos de fitness por parte dos consumidores. Além disso, os resultados revelaram que a auto­estima do consumidor também não modera o efeito da atractividade sobre a intenção de compra. Esta tese contribui para a comunidade académica ao fornecer um ponto de partida para mais investigação sobre os atributos físicos dos influenciadores das redes sociais que possam ter um impacto na intenção de compra no emergente mercado de fitness

Social Networks Influence Analysis

Pew Research Center estimates that as of 2014, 74% of the Internet Users used social media, i.e., more than 2.4 billion users. With the growing popularity of social media where Internet users exchange their opinions on many things including their daily life encounters, it is not surprising that many organizations are interested in learning what users say about their products and services. To be able to play a proactive role in steering what user’s say, many organizations have engaged in efforts aiming at identifying efficient ways of marketing certain products and services, and making sure user reviews are somewhat favorable. Favorable reviews are typically achieved through identifying users on social networks who have a strong influence power over a large number of other users, i.e. influential users. Twitter has emerged as one of the prominent social network services with 320 million monthly active users worldwide. Based on the literature, influential Twitter users have been typically analyzed using the following three models: topic-based model, topology-based model, and user characteristics-based model. The topology-based model is criticized for being static, i.e., it does not adapt to the social network changes such as user’s new posts, or new relationships. The user characteristics-based model was presented as an alternative approach; however, it was criticized for discounting the impact of interactions between users, and users’ interests. Lastly, the topic-based model, while sensitive to users’ interests, typically suffers from ignoring the inclusion of inter-user interactions. This thesis research introduces a dynamic, comprehensive and topic-sensitive approach for identifying social network influencers leveraging the strengths of the aforementioned models. Three separate experiments were conducted to evaluate the new approach using the information diffusion measure. In these experiments, software was developed to capture users’ tweets pertinent to a topic over a period of time, and store the tweet’s metadata in a relational database. A graph representing users was extracted from the database. The new approach was applied to the users’ graph to compute an influence score for each user. Results show that the new composite influence score is more accurate in comprehensively identifying true influential users, when compared to scores calculated using the characteristics-based, topic-based, and topology-based models. Also, this research shows that the new approach could leverage a variety of machine learning algorithms to accurately identify influencers. Last, while the focus of this research was on Twitter, our approach may be applicable to other social networks and micro-blogging services

Who Contributes to the Knowledge Sharing Economy?

Information sharing dynamics of social networks rely on a small set of influencers to effectively reach a large audience. Our recent results and observations demonstrate that the shape and identity of this elite, especially those contributing \emph{original} content, is difficult to predict. Information acquisition is often cited as an example of a public good. However, this emerging and powerful theory has yet to provably offer qualitative insights on how specialization of users into active and passive participants occurs. This paper bridges, for the first time, the theory of public goods and the analysis of diffusion in social media. We introduce a non-linear model of \emph{perishable} public goods, leveraging new observations about sharing of media sources. The primary contribution of this work is to show that \emph{shelf time}, which characterizes the rate at which content get renewed, is a critical factor in audience participation. Our model proves a fundamental \emph{dichotomy} in information diffusion: While short-lived content has simple and predictable diffusion, long-lived content has complex specialization. This occurs even when all information seekers are \emph{ex ante} identical and could be a contributing factor to the difficulty of predicting social network participation and evolution.Comment: 15 pages in ACM Conference on Online Social Networks 201

Who are Portuguese followers of social media influencers (SMIs), and their attitudes towards SMIs? An exploratory study

Influencers serve as crucial role models, influencing the behavior, aesthetics, and ideologies of their followers. This cross-sectional study aims to explore the perspectives of Portuguese social media users toward influencers. Data were collected through a self-administered questionnaire from 759 participants obtained through snowball sampling. The majority (75.5%) were female, averaging 26 years in age. Descriptive statistics, mean comparisons, and correlations were utilized for analysis. Portuguese followers of social media influencers, primarily consisting of young women with lower formal education, are active on platforms like Facebook, Instagram, and Youtube. They spend considerable time on social media, engaging with influencers through actions such as liking or tagging friends. Fashion and beauty influencers are particularly favored. Followers value influencers who interact with them, appreciate personal posts and disclosures, and form parasocial relationships with influencers. While many express a willingness to purchase products promoted by influencers, a noteworthy portion hasn't made such purchases. Participants express uncertainty about the guaranteed quality of products endorsed by influencers, yet 36.5% acknowledge the significance of influencers in discovering new products or trends.This study provides valuable insights for influencers and brands targeting a specific audience. It also underscores potential concerns for followers, emphasizing the link between excessive social media use and problematic behavior.info:eu-repo/semantics/publishedVersio

The impact of the luxury influencer's background and story on women's luxury purchase intention and conscientiousness as a moderator

The purpose of this thesis is to determine whether the background and story of luxury influencers affect women's luxury items purchase intention, while taking the conscientiousness personality trait into consideration. Conscientiousness is addressed in this thesis since research demonstrates that conscientiousness individuals are self-disciplined and hence less likely to engage with luxury items. The influencer identification, purchase intention, and conscientiousness scale were measured and used to better assess the effect of the background and influencer story on purchase intention. An online survey was conducted to gather information, and 86 valid answers were received. The current research demonstrated no significant impact of the background and stories of luxury influencers on customers' purchasing intentions for luxury items. Besides, results demonstrated that consumer conscientiousness did not moderate the effect between the backgrounds of luxury influencers and their impact on customers' purchase intention for luxury product. By examining a new approach, this thesis contributes to academic knowledge and management decision-making by improving our understanding of the impact of influencers' stories and their ability to engage consumers and influence their purchase intention in the emerging luxury market, as well as by providing a deeper understanding of the role of conscientiousness as a personality trait in the purchase decision.O objectivo desta tese é determinar se os antecedentes e a história dos influenciadores de luxo afectam a intenção de compra de artigos de luxo das mulheres, tendo em consideração o traço de personalidade conscienciosidade. A conscienciosidade é abordada nesta tese, uma vez que a investigação demonstra que os indivíduos conscienciosos são autodisciplinados e, por conseguinte, menos susceptíveis de se envolverem com artigos de luxo. A identificação do influenciador, a intenção de compra e a escala de conscienciosidade foram medidas e utilizadas para avaliar melhor o efeito dos antecedentes e da história do influenciador na intenção de compra. Foi realizado um inquérito online para recolher informações, tendo sido recebidas 86 respostas válidas. A presente investigação não demonstrou qualquer impacto significativo dos antecedentes e das histórias dos influenciadores de luxo nas intenções de compra de artigos de luxo por parte dos clientes. Além disso, os resultados demonstraram que a conscienciosidade do consumidor não moderou o efeito entre os antecedentes dos influenciadores de luxo e o seu impacto na intenção de compra de produtos de luxo por parte dos clientes. Ao investigar uma nova abordagem, esta tese contribui para o conhecimento académico e para a tomada de decisões de gestão, melhorando a nossa compreensão do impacto das histórias dos influenciadores e da sua capacidade de envolver os consumidores e influenciar a sua intenção de compra no mercado de luxo emergente, bem como proporcionando uma compreensão mais profunda do papel da conscienciosidade como traço de personalidade na decisão de compra

Analyzing digital societal interactions and sentiment classification in Twitter (X) during critical events in Chile

This study explores the influence of social media content on societal attitudes and actions during critical events, with a special focus on occurrences in Chile, such as the COVID-19 pandemic, the 2019 protests, and the wildfires in 2017 and 2023. By leveraging a novel tweet dataset, this study introduces new metrics for assessing sentiment, inclusivity, engagement, and impact, thereby providing a comprehensive framework for analyzing social media dynamics. The methodology employed enhances sentiment classification through the use of a Deep Random Vector Functional Link (D-RVFL) neural network, which demonstrates superior performance over traditional models such as Support Vector Machines (SVM), naive Bayes, and back propagation (BP) neural networks, achieving an overall average accuracy of 78.30% (0.17). This advancement is attributed to deep learning techniques with direct input–output connections that facilitate faster and more precise sentiment classification. This analysis differentiates the roles of influencers, press radio, and television handlers during crises, revealing how various social media actors affect information dissemination and audience engagement. By dissecting online behaviors and classifying sentiments using the RVFL network, this study sheds light on the effects of the digital landscape on societal attitudes and actions during emergencies. These findings underscore the importance of understanding the nuances of social media engagement to develop more effective crisis communication strategies