Discovering conversational topics and emotions associated with Demonetization tweets in India

Social media platforms contain great wealth of information which provides us opportunities explore hidden patterns or unknown correlations, and understand people's satisfaction with what they are discussing. As one showcase, in this paper, we summarize the data set of Twitter messages related to recent demonetization of all Rs. 500 and Rs. 1000 notes in India and explore insights from Twitter's data. Our proposed system automatically extracts the popular latent topics in conversations regarding demonetization discussed in Twitter via the Latent Dirichlet Allocation (LDA) based topic model and also identifies the correlated topics across different categories. Additionally, it also discovers people's opinions expressed through their tweets related to the event under consideration via the emotion analyzer. The system also employs an intuitive and informative visualization to show the uncovered insight. Furthermore, we use an evaluation measure, Normalized Mutual Information (NMI), to select the best LDA models. The obtained LDA results show that the tool can be effectively used to extract discussion topics and summarize them for further manual analysis.Comment: 6 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:1608.02519 by other authors; text overlap with arXiv:1705.08094 by other author

How Do People View COVID-19 Vaccines

The COVID-19 pandemic has been the most devastating public health crisis in the recent decade and vaccination is anticipated as the means to terminate the pandemic. People's views and feelings over COVID-19 vaccines determine the success of vaccination. This study was set to investigate sentiments and common topics about COVID-19 vaccines by machine learning sentiment and topic analyses with natural language processing on massive tweets data. Findings revealed that concern on COVID-19 vaccine grew alongside the introduction and start of vaccination programs. Overall positive sentiments and emotions were greater than negative ones. Common topics include vaccine development for progression, effectiveness, safety, availability, sharing of vaccines received, and updates on pandemics and government policies. Outcomes suggested the current atmosphere and its focus over the COVID-19 vaccine issue for the public health sector and policymakers for better decision-making. Evaluations on analytical methods were performed additionally

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

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pHealth 2021. Proc. of the 18th Internat. Conf. on Wearable Micro and Nano Technologies for Personalised Health, 8-10 November 2021, Genoa, Italy

Smart mobile systems – microsystems, smart textiles, smart implants, sensor-controlled medical devices – together with related body, local and wide-area networks up to cloud services, have become important enablers for telemedicine and the next generation of healthcare services. The multilateral benefits of pHealth technologies offer enormous potential for all stakeholder communities, not only in terms of improvements in medical quality and industrial competitiveness, but also for the management of healthcare costs and, last but not least, the improvement of patient experience. This book presents the proceedings of pHealth 2021, the 18th in a series of conferences on wearable micro and nano technologies for personalized health with personal health management systems, hosted by the University of Genoa, Italy, and held as an online event from 8 – 10 November 2021. The conference focused on digital health ecosystems in the transformation of healthcare towards personalized, participative, preventive, predictive precision medicine (5P medicine). The book contains 46 peer-reviewed papers (1 keynote, 5 invited papers, 33 full papers, and 7 poster papers). Subjects covered include the deployment of mobile technologies, micro-nano-bio smart systems, bio-data management and analytics, autonomous and intelligent systems, the Health Internet of Things (HIoT), as well as potential risks for security and privacy, and the motivation and empowerment of patients in care processes. Providing an overview of current advances in personalized health and health management, the book will be of interest to all those working in the field of healthcare today

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

Understanding Customer Switching Behaviour in the Retail Banking Sector: The Case of Nigeria and the Gambia

This thesis examines customer switching behaviour in Nigeria and Gambia, focusing on the retail banking sector. The study’s key objective is to provide new knowledge on customer banking behaviour in the retail banking sector. The study is grounded in Bansal et al.’s (2005) push-pull-mooring model. A qualitative method was employed in the data collection, incorporating a triangulation approach, whereby direct observations were combined with thematic interviews and focus group discussions. The intention behind this method was to increase the validity of the research results. Ultimately, the study findings indicate significant factors and subfactors influencing customer switching behaviour in the retail banking sector. The results are categorised as push, pull, or mooring factors. It identifies seven push factors with thirteen subfactors, four pull factors with ten subfactors, and six mooring factors with three subfactors. The study’s significant contribution to existing knowledge of services marketing is the identification of new and emerging constructs, thus extending the existing knowledge in the literature. The study’s findings support numerous results of prior relevant research, while some findings disagree with those of previous research. Furthermore, the new constructs that emerge from this research are highly relevant to today’s consumers. For example, factors like banking products, perceived knowledge of banking products, perceived relative security of banking products, satisfaction with the current bank, emotions (e.g., regret or anger), liquidity challenges, bank staff career development prospects, and ethical banking issues are the study’s unique contributions to the push factors and subfactors. In addition, the emerging pull factors and subfactors include technological advancement, coronavirus pandemic-induced switching, a bank’s physical appearance, positive banking expectations, a bank’s relative proximity, expected switching benefits, perceived usefulness of a bank’s digital platforms, perceived ease of banking transactions, personalised banking offerings, and repositioning banking business models. Lastly, the new mooring factors and subfactors identified in this study are inertia, changes in customer needs or tastes, involuntary switching, and bank responsiveness. Consequently, the author has developed a framework/model based on the findings of this study. The new framework/model presented comprehensive results with practical implications and a valuable contribution to the current knowledge of customer switching behaviour

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

Draw My Life: An analysis of the quantity and typology of emotional linguistic content in self-identified female and male YouTubers’ life narratives

La presente investigación tiene como objetivo determinar similitudes y diferencias en la cantidad y tipología de expresiones relacionadas con la emoción – referencias tanto implícitas como explícitas a “feelings, moods and all kinds of affective experience” [sentimientos, estados de ánimo y todo tipo de experiencias afectivas] (Mackenzie y Alba-Juez, 2019, p. 15) – de 100 personas autoidentificadas como mujeres (con un corpus de 248.613 palabras en total) y 100 personas autoidentificadas como hombres (con un corpus de 227.979 palabras en total) en sus vídeos autobiográficos dentro del género Draw My Life de YouTube. El proyecto se sustenta en la noción de Lutz (1990, p. 151) de que “any discourse on emotion is also, at least implicitly, a discourse on gender” [cualquier discurso sobre la emoción es también, al menos implícitamente, un discurso sobre género], con frecuentes suposiciones en investigaciones previas sobre las expectativas sociales relacionadas con la “greater emotional expressivity” [mayor expresividad emocional] de las mujeres (Chaplin, 2015, p. 14) y la “restrictive emotionality” [emocionalidad restrictiva] de los hombres (O’Neil, Good, & Holmes, 1995, p. 176). Con el objetivo de obtener datos completos y fiables sobre las expresiones relacionadas con las emociones de los YouTubers femeninos y masculinos, el estudio combina métodos de investigación cuantitativos y cualitativos que se basan en varias herramientas computerizadas, así como en procesos de anotación manual. En particular, se adopta un marco de análisis crítico del discurso basado en corpus, motivado por la suposición de Baker et al. (2008, p. 227) de que las investigaciones de Lingüística de Corpus “offer the researcher a reasonably high degree of objectivity; that is, they enable the researcher to approach the texts (or text surface) (relatively) free from any preconceived or existing notions regarding their linguistic or semantic/pragmatic content” [ofrecen al investigador un grado razonablemente alto de objetividad; es decir, permiten al investigador acercarse a los textos (o la superficie del texto) (relativamente) libre de cualquier noción preconcebida o existente sobre su contenido lingüístico o semántico/ pragmático]. El trabajo se enmarca dentro del dominio de los Estudios de Discurso Asistidos por Corpus, definido por Partington, Duguid y Taylor (2013, p. 10) como “that set of studies into the form and/or function of language which incorporate the use of computerised corpora in their analysis” [ese conjunto de estudios sobre la forma y/o la función del lenguaje que incorporan el uso de corpus informatizados en su análisis”]. Las herramientas informáticas específicas que se utilizan en el análisis de los datos de Draw My Life relacionados con sentimientos/emociones son Lingmotif, LIWC2015 (Linguistic Inquiry and Word Count) y Wmatrix4