68 research outputs found

    Social media mental health analysis framework through applied computational approaches

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    Studies have shown that mental illness burdens not only public health and productivity but also established market economies throughout the world. However, mental disorders are difficult to diagnose and monitor through traditional methods, which heavily rely on interviews, questionnaires and surveys, resulting in high under-diagnosis and under-treatment rates. The increasing use of online social media, such as Facebook and Twitter, is now a common part of people’s everyday life. The continuous and real-time user-generated content often reflects feelings, opinions, social status and behaviours of individuals, creating an unprecedented wealth of person-specific information. With advances in data science, social media has already been increasingly employed in population health monitoring and more recently mental health applications to understand mental disorders as well as to develop online screening and intervention tools. However, existing research efforts are still in their infancy, primarily aimed at highlighting the potential of employing social media in mental health research. The majority of work is developed on ad hoc datasets and lacks a systematic research pipeline. [Continues.]</div

    Social Media Analysis for Social Good

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    Data on social media is abundant and offers valuable information that can be utilised for a range of purposes. Users share their experiences and opinions on various topics, ranging from their personal life to the community and the world, in real-time. In comparison to conventional data sources, social media is cost-effective to obtain, is up-to-date and reaches a larger audience. By analysing this rich data source, it can contribute to solving societal issues and promote social impact in an equitable manner. In this thesis, I present my research in exploring innovative applications using \ac{NLP} and machine learning to identify patterns and extract actionable insights from social media data to ultimately make a positive impact on society. First, I evaluate the impact of an intervention program aimed at promoting inclusive and equitable learning opportunities for underrepresented communities using social media data. Second, I develop EmoBERT, an emotion-based variant of the BERT model, for detecting fine-grained emotions to gauge the well-being of a population during significant disease outbreaks. Third, to improve public health surveillance on social media, I demonstrate how emotions expressed in social media posts can be incorporated into health mention classification using an intermediate task fine-tuning and multi-feature fusion approach. I also propose a multi-task learning framework to model the literal meanings of disease and symptom words to enhance the classification of health mentions. Fourth, I create a new health mention dataset to address the imbalance in health data availability between developing and developed countries, providing a benchmark alternative to the traditional standards used in digital health research. Finally, I leverage the power of pretrained language models to analyse religious activities, recognised as social determinants of health, during disease outbreaks

    Pragmatic borrowing between English and Chinese: A comparative study of two-way exchanges

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    Through centuries of cross-cultural communication, English has been enriched by elements from other languages around the world, including Chinese; meanwhile, English has also exerted considerable influence on the Chinese language. Lexical exchanges between the two languages have been studied in previous research, and yet are mostly restricted to the lexical items themselves. This thesis particularly explores the pragmatic aspect of this language contact, examining items that are used to convey attitudinal or interpersonal meanings. I conduct a series of case studies on bi-directional pragmatic borrowing between English and Chinese, using a variety of data sources, which include dictionaries, corpora, social media data, and other online resources. I take a broad view of what constitutes pragmatic borrowing: I not only investigate the borrowing and integration of discourse-pragmatic items that are transferred between the two languages, but also examine the pragmatic motivations for the borrowing of other lexical items and even grammatical units. The items discussed in the thesis range from parts of words, specifically affixes, to individual words to longer structures, and contextual analysis shows that all of these have been used to achieve pragmatic effects. The study demonstrates the important role of cultural context, speaker creativity, and sociolinguistic factors in the borrowing, integration, and innovative use of linguistic items

    Optimising Emotions, Incubating Falsehoods: How to Protect the Global Civic Body from Disinformation and Misinformation

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    This open access book deconstructs the core features of online misinformation and disinformation. It finds that the optimisation of emotions for commercial and political gain is a primary cause of false information online. The chapters distil societal harms, evaluate solutions, and consider what must be done to strengthen societies as new biometric forms of emotion profiling emerge. Based on a rich, empirical, and interdisciplinary literature that examines multiple countries, the book will be of interest to scholars and students of Communications, Journalism, Politics, Sociology, Science and Technology Studies, and Information Science, as well as global and local policymakers and ordinary citizens interested in how to prevent the spread of false information worldwide, both now and in the future

    Optimising Emotions, Incubating Falsehoods

    Get PDF
    This open access book deconstructs the core features of online misinformation and disinformation. It finds that the optimisation of emotions for commercial and political gain is a primary cause of false information online. The chapters distil societal harms, evaluate solutions, and consider what must be done to strengthen societies as new biometric forms of emotion profiling emerge. Based on a rich, empirical, and interdisciplinary literature that examines multiple countries, the book will be of interest to scholars and students of Communications, Journalism, Politics, Sociology, Science and Technology Studies, and Information Science, as well as global and local policymakers and ordinary citizens interested in how to prevent the spread of false information worldwide, both now and in the future
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