Guide to Recruiting Black Men as Mentors for Black Boys

Black men are uniquely positioned to help guide black male youth to educational success and a productive future and through the barriers that stand in their way. But there are almost always more black boys to be mentored than black men to mentor them in formal mentoring programs. This guide helps mentoring programs engage in a productive and inclusive recruitment campaign by: 1) addressing program readiness; and 2) providing guidance on an effective social marketing campaign

Designing electronic collaborative learning environments

Electronic collaborative learning environments for learning and working are in vogue. Designers design them according to their own constructivist interpretations of what collaborative learning is and what it should achieve. Educators employ them with different educational approaches and in diverse situations to achieve different ends. Students use them, sometimes very enthusiastically, but often in a perfunctory way. Finally, researchers study them and—as is usually the case when apples and oranges are compared—find no conclusive evidence as to whether or not they work, where they do or do not work, when they do or do not work and, most importantly, why, they do or do not work. This contribution presents an affordance framework for such collaborative learning environments; an interaction design procedure for designing, developing, and implementing them; and an educational affordance approach to the use of tasks in those environments. It also presents the results of three projects dealing with these three issues

Why Pass On Fashion Viral Message? The Moderating Role of Consumers’ Fashion Traits, Message Traits and Individual Dynamics Traits in Social Media

Social media is being used as platforms for viral marketing. Although there is some evidence on the usefulness of viral marketing from the marketers’ perspective, little is known about the motivations, attitudes, and behaviors of consumers engaged in this marketing instrument. As the social media platform continues to grow, understanding the characteristics and motivations of key players is invaluable for marketers and communicators who deal with message strategy and media outreach. Fashion companies have noticed this change and want to be present in the social media in different ways. This research represents a comprehensive attempt to examine the factors that impact on consumer usage of social media and their behavioral intentions to forward fashion viral messages by developing an attitudinal model that integrated uses and gratification theory and elaboration likelihood model; proposing that the relationship is moderated by individual dynamic traits, message traits and consumer fashion traits. Empirical data was collected from a convenience sample of 381 college students in two southeastern universities via an online survey. Validity and reliability of research scales were assessed. Hypothesized relationships and moderating effects were tested using two-step structural equation modeling approach. Within the general model the findings show that individuals will forward a fashion viral message if they have stronger favorable utilitarian and value-expressive attitudes towards the message. Motivations did not significantly impact attitudes of the consumer with an exception of the dimension of interpersonal utility that impacts individual’s value expressive attitude. The results of moderating variables indicate that message traits (functional and experiential oriented) impact consumers’ utilitarian and value-expressive attitudes. In relation to consumer fashion traits, there was no significant difference among consumers with high or low fashion leadership and those with high or low fashion involvement. Individual dynamics traits (viral dynamics and structural social capital) showed some moderating effects on the relationships between motivations and attitudes toward a social media marketing message. The results add to existing literature related to viral marketing and validate the claim that viral marketing can be used for marketing purposes resulting in increased business for firms. Theoretical and practical implications were provided based on research findings

Temporal Emotion Dynamics in Social Networks

[ES] El análisis de sentimientos en redes sociales se ha estudiado ampliamente durante la última década. A pesar de ello, las distintas categorías de sentimientos no se consideran adecuadamente en muchos casos, y el estudio de patrones de difusión de las emociones es limitado. Por lo tanto, comprender la importancia de emociones específicas será más beneficioso para diversas actividades de marketing, toma de decisiones empresariales y campañas políticas. Esta tesis doctoral se centra en el diseño de un marco teórico para analizar el amplio espectro de sentimientos y explicar cómo se propagan las emociones utilizando conceptos de redes temporales y multicapa. Particularmente, nuestro objetivo es proporcionar información sobre el modelado de la influencia de las emociones y como esta afecta a los problemas de estimación de las emociones y a la naturaleza dinámica temporal en la conversación social. Para mostrar la eficacia del modelo propuesto, se han recopilado publicaciones relacionadas con diferentes eventos de Twitter y hemos construido una estructura de red temporal sobre la conversación. En primer lugar, realizamos un análisis de sentimientos adoptando un enfoque basado en el léxico y en el modelo circunflejo de emociones de Russell que mejora la efectividad de la caracterización del sentimiento. A partir de este análisis investigamos la dinámica social de las emociones presente en las opiniones de los usuarios analizando diferentes características de influencia social. A continuación, diseñamos un modelo estocástico temporal basado en emociones para investigar el patrón de participación de los usuarios y predecir las emociones significativas. Nuestra contribución final es el desarrollo de un modelo de influencia secuencial basado en emociones mediante la utilización de redes neuronales recurrentes que permiten predecir emociones de una manera más completa. Finalmente, el documento presenta algunas conclusiones y también describe las direcciones de investigación futuras.[CA] L'anàlisi de sentiments en xarxes socials s'ha estudiat àmpliament durant l'última dècada. Malgrat això, les diferents categories de sentiments no es consideren adequadament en molts casos, i l'estudi de patrons de difusió de les emocions és limitat. Per tant, comprendre la importància d'emocions específiques serà més beneficiós per a diverses activitats de màrqueting, presa de decisions empresarials i campanyes polítiques. Aquesta tesi doctoral se centra en el disseny d'un marc teòric per a analitzar l'ampli espectre de sentiments i explicar com es propaguen les emocions utilitzant conceptes de xarxes temporals i multicapa. Particularment, el nostre objectiu és proporcionar informació sobre el modelatge de la influència de les emocions i com aquesta afecta als problemes d'estimació de les emocions i a la naturalesa dinàmica temporal en la conversa social. Per a mostrar l'eficàcia del model proposat, s'han recopilat publicacions relacionades amb diferents esdeveniments de Twitter i hem construït una estructura de xarxa temporal sobre la conversa. En primer lloc, realitzem una anàlisi de sentiments adoptant un enfocament basat en el lèxic i en el model circumflex d'emocions de Russell que millora l'efectivitat de la caracterització del sentiment. A partir d'aquesta anàlisi investiguem la dinàmica social de les emocions present en les opinions dels usuaris analitzant diferents característiques d'influència social. A continuació, dissenyem un model estocàstic temporal basat en emocions per a investigar el patró de participació dels usuaris i predir les emocions significatives. La nostra contribució final és el desenvolupament d'un model d'influència seqüencial basat en emocions mitjançant la utilització de xarxes neuronals recurrents que permeten predir emocions d'una manera més completa. Finalment, el document presenta algunes conclusions i també descriu les direccions d'investigació futures.[EN] Sentiment analysis in social networks has been widely analysed over the last decade. Despite the amount of research done in sentiment analysis in social networks, the distinct categories are not appropriately considered in many cases, and the study of dissemination patterns of emotions is limited. Therefore, understanding the significance of specific emotions will be more beneficial for various marketing activities, policy-making decisions and political campaigns. The current PhD thesis focuses on designing a theoretical framework for analyzing the broad spectrum of sentiments and explain how emotions are propagated using concepts from temporal and multilayer networks. More precisely, our goal is to provide insights into emotion influence modelling that solves emotion estimation problems and its temporal dynamics nature on social conversation. To exhibit the efficacy of the proposed model, we have collected posts related to different events from Twitter and build a temporal network structure over the conversation. Firstly, we perform sentiment analysis with the adaptation of a lexicon-based approach and the circumplex model of affect that enhances the effectiveness of the sentiment characterization. Subsequently, we investigate the social dynamics of emotion present in users' opinions by analyzing different social influential characteristics. Next, we design a temporal emotion-based stochastic model in order to investigate the engagement pattern and predict the significant emotions. Our ultimate contribution is the development of a sequential emotion-based influence model with the advancement of recurrent neural networks. It offers to predict emotions in a more comprehensive manner. Finally, the document presents some conclusions and also outlines future research directions.Naskar, D. (2022). Temporal Emotion Dynamics in Social Networks [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/180997TESI

Risk Perception and Drug Safety Evaluation

The authors present a Risk communication framework based on a survey of empirical research concerning public Risk perceptions. They also apply it to the area of pharmaceutical regulation to suggest more effective regulatory strategies

Stigmergy in Web 2.0: a model for site dynamics

Building Web 2.0 sites does not necessarily ensure the success of the site. We aim to better understand what improves the success of a site by drawing insight from biologically inspired design patterns. Web 2.0 sites provide a mechanism for human interaction enabling powerful intercommunication between massive volumes of users. Early Web 2.0 site providers that were previously dominant are being succeeded by newer sites providing innovative social interaction mechanisms. Understanding what site traits contribute to this success drives research into Web sites mechanics using models to describe the associated social networking behaviour. Some of these models attempt to show how the volume of users provides a self-organising and self-contextualisation of content. One model describing coordinated environments is called stigmergy, a term originally describing coordinated insect behavior. This paper explores how exploiting stigmergy can provide a valuable mechanism for identifying and analysing online user behavior specifically when considering that user freedom of choice is restricted by the provided web site functionality. This will aid our building better collaborative Web sites improving the collaborative processes