Usage of Facebook by Student Leaders in Creating Awareness Regarding Covid-19 in Guwahati

Pandemic like COVID-19 has triggered disruptions in personal and collective lives globally. It is not only a pandemic, but also an Infodemic of misinformation about the virus which raises demand for reliable and trustworthy information. With the advent of social media creation and consumption of news have been changing among the young generation. Student leaders have taken on additional work and assumed new responsibilities by volunteering in their communities and creating awareness among the public about the accuracy of information and measures to be taken against the deadly virus. This study explores the use of Facebook handles by the student leaders of two universities in Guwahati in creating awareness about the health-related messages regarding Covid-19 and its vaccination. The researcher will use critical discourse analysis to evaluate the use of social networking sites by the students’ leaders. To understand the usage by the leaders, Facebook pages of the leaders would be followed and studied backed with unstructured interviews with the leaders to understand the purpose of and pattern of using the social media handles.

Dante's Gluttons

Dante’s Gluttons: Food and Society from the Convivio to the Comedy explores how in his work medieval Italian poet Dante Alighieri (1265-1321) uses food to articulate, reinforce, criticize, and correct the social, political, and cultural values of his time. Combining medieval history, food studies, and literary criticism, Dante’s Gluttons historicizes food and eating in Dante, beginning in his earliest collected poetry and arriving at the end of his major work. For Dante, the consumption of food is not a frivolity, but a crux of life in the most profound sense of the term, and gluttony is the abdication of civic and spiritual responsibility and a danger to the individual body and soul as well as to the collective. This book establishes how one of the world’s preeminent authors uses the intimacy and universality of food as a touchstone, communicating through a gastronomic language rooted in the deeply human relationship with material sustenance.

Valuing the local within the global: A discourse analysis of professional development in a U.S.-Kurdish transnational university partnership

In an effort to support higher education in developing countries, partnerships between U.S. and international universities have surged, raising questions concerning the social equity of such linkages. Using a New Literacy Studies approach to discourse analysis, online transcripts from one such university partnership were analyzed to determine how language was used to negotiate a more equitable partnership through the adaptation of the social context of professional development activities. Discourse analysis of three relevant linguistic markers in the data suggests that cultural perspectives on professional development influenced the language choices made by university partners, reshaping the power structure toward greater social equity, and aiding in the completion of joint professional development goals. Findings underscore the importance of drawing on local knowledges in planning for and conducting transnational university partnerships.

Self-Aware Contextual Behavior Analysis for Service Quality Assurance Over Social Networks

Social media allows people to share their ideologue through an efficient channel of communication. The social dialogues carry sentiment in expression regarding a particular social profile, trend, or topic. In our research, we have collected real-time user comments and feedbacks from Twitter portals of two food delivery services. This is followed by the extraction of the most prevalent contexts using natural language analytics. Further, our proposed algorithmic framework is used to generate a signed social network to analyze the product-centric behavioral sentiment. Analysis of sentiment with the fine-grained level about contexts gave a broader view to evaluate and perform contextual predictions. Customer behavior is analyzed, and the outcome is received in terms of positive and negative contexts. The results from our social behavioral model predicted the positive and negative contextual sentiments of customers, which can be further used to help in deciding future strategies and assuring service quality for better customer satisfaction.

On the Aggression Diffusion Modeling and Minimization in Twitter

Aggression in online social networks has been studied mostly from the perspective of machine learning, which detects such behavior in a static context. However, the way aggression diffuses in the network has received little attention as it embeds modeling challenges. In fact, modeling how aggression propagates from one user to another is an important research topic, since it can enable effective aggression monitoring, especially in media platforms, which up to now apply simplistic user blocking techniques. In this article, we address aggression propagation modeling and minimization in Twitter, since it is a popular microblogging platform at which aggression had several onsets. We propose various methods building on two well-known diffusion models, Independent Cascade ( IC ) and Linear Threshold ( LT ), to study the aggression evolution in the social network. We experimentally investigate how well each method can model aggression propagation using real Twitter data, while varying parameters, such as seed users selection, graph edge weighting, users’ activation timing, and so on. It is found that the best performing strategies are the ones to select seed users with a degree-based approach, weigh user edges based on their social circles’ overlaps, and activate users according to their aggression levels. We further employ the best performing models to predict which ordinary real users could become aggressive (and vice versa) in the future, and achieve up to AUC = 0.89 in this prediction task. Finally, we investigate aggression minimization by launching competitive cascades to “inform” and “heal” aggressors. We show that IC and LT models can be used in aggression minimization, providing less intrusive alternatives to the blocking techniques currently employed by Twitter.

HuDA_COVID Human Disposition Analysis during COVID-19 using Machine Learning

Coronavirus has greatly impacted various aspects of human life, including human psychology & human disposition. In this paper, we attempted to analyze the impact of the COVID-19 pandemic on human health. We propose Human Disposition Analysis during COVID-19 using machine learning (HuDA_COVID), where factors such as age, employment, addiction, stress level are studied for human disposition analysis. A mass survey is conducted on individuals of various age groups, regions & professions, and the methodology achieved varied accuracy ranges of 87.5% to 98%. The study shows people are worried about lockdown, work & relationships. Furthermore, 23% of the respondents have not had any effect. 45% and 32% have had positive and negative effects, respectively. It is a novel study in human disposition analysis in COVID-19 where a novel weighted assignment indicating the health status is also proposed. HuDA_COVID clearly indicates a need for a methodical approach towards the human psychological needs to help the social organizations formulating holistic interventions for affected individuals.

From Collaborative Habituation to Everyday Togetherness: A Long-Term Study of Use of the Messaging Kettle

We present a long-term study of use of the Messaging Kettle, an Internet of Things (IOT) research prototype that augments an everyday kettle with both sensing and messaging capability and a beautiful light display in order to investigate connecting geographically distant loved ones to their family through the routine of boiling the kettle. Connection at a distance has been of sustained interest to the CHI community, and the social connection of older people is of increasing importance in recognition of ageing populations globally. However, very few novel designs in this domain have been investigated in situ or over the long term to examine whether their use sustains, and if so, how they impact communication in a relationship. The Messaging Kettle was trialled with four pairs of dispersed older mothers and adult daughters over timeframes that lasted between two months to more than two years. We observed the phenomenon of collaborative habituation wherein each party creatively made the technology work for them both through a combination of the gradual transformation of their everyday practices, arrangements, and living. Through developing these joint practices over time, participants expressed feelings of everyday togetherness that nurture their relationship at a distance. Three of the four couples continued to use the prototype for years, beyond the initial trial. We reflect on the artful integration of features of the Messaging Kettle and the way in which these features supported collaborative habituation . We also reflect on lessons and implications for the design of such relational technologies.