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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7...70 Hits 41 – 60 of 1.400 41 Event parsing and the origins of grammar Zuberbühler, Klaus. - 2021 BASE Show details 42 Chimpanzees combine pant hoots with food calls into larger structures Leroux, Maël; Bosshard, Alexandra B.; Chandia, Bosco. - 2021 BASE Show details 43 Spatial agency bias and word order flexibility : a comparison of 14 European languages Suitner, Caterina; Maass, Anne; Navarrete, Eduardo. - 2021 BASE Show details 44 Studying the behavioural, physiological, and neural indices of associative learning in multi-trial paradigms: methodological and analytical considerations Jambazova, Antonia Antony. - 2021 BASE Show details 45 Improving video game conversations with trope-informed design Rennick, Stephanie; Roberts, Sean. - : Game Studies, 2021 BASE Show details 46 A lexicon-based approach to detecting suicide-related text on Twitter. Sarsam, Samer Muthana; Al-Samarraie, Hosam; Alzahrani, Ahmed Ibrahim. - : Elsevier, 2021 BASE Show details 47 A lexicon-based approach to detecting suicide-related text on Twitter. Sarsam, Samer Muthana; Al-Samarraie, Hosam; Alzahrani, Ahmed Ibrahim; Alnumay, Aleed; Smith, Andrew Paul. - : Elsevier, 2021 Abstract: Expression of emotion is an indicator that can contribute to the detection of mental health-related disorders. Suicide causes death to many people around the globe, and despite the suicide prevention strategies that have been employed over the years, only a few studies have explored the role of emotions in predicting suicidal behavior on social media platforms. This study explored the role of emotions from Twitter messages in detecting suicide-related content. We extracted and analyzed the characteristics of Twitter users' sentiment and behavior response (anger, fear, sadness, joy, positive, and negative) using NRC Affect Intensity Lexicon and SentiStrength techniques. A semi-supervised learning method was applied using the YATSI classifier or “Yet Another Two-Stage Idea” to efficiently recognize suicide-related tweets. The results showed that tweets associated with suicide content were exclusively related to fear, sadness, and negative sentiments. The classification results showed the potential of emotions in facilitating the detection of suicide-related content online. Our findings offer valuable insights into ongoing research on the prevention of suicide risk and other mental-related disorders on Twitter. The proposed mechanism can contribute to the development of clinical decision support systems that deal with evidence-based guidelines and generate customized recommendations. Keyword: BF Psychology URL: https://orca.cardiff.ac.uk/137402/1/A%20lexicon-based%20approach%20to%20detecting%20suicide-related%20messages%20on%20Twitter%20_%20Post-print.pdf https://orca.cardiff.ac.uk/137402/ https://doi.org/10.1016/j.bspc.2020.102355 BASE Hide details 48 Functional and structural properties of spatial processing networks in the brain Read, Marie-Lucie. - 2021 BASE Show details 49 Investigating the role of image meaning and prior knowledge in human eye movements control Pedziwiatr, Marek. - 2021 BASE Show details 50 The “Good is Up” metaphoric effects on recognition: True for source guessing but false for item memory Jin, Zixi. - 2021 BASE Show details 51 Using an educational psychologist led psychoeducation group skills intervention to develop the emotion regulation skills of further education students Bignell, Hilary. - 2021 BASE Show details 52 Individual differences in neural architecture supporting mental time travel Ridgeway, Samuel. - 2021 BASE Show details 53 Group interventions for the reduction of psychological distress in university students Butler, John. - 2021 BASE Show details 54 Statistical and sequence learning lead to persistent memory in children after a one-year offline period Toth-Faber, Eszter; Janacsek, Karolina; Nemeth, Dezso. - : Nature, 2021 BASE Show details 55 Empowering communication through speaking, reading and writing Reynolds, Deborah; Smith, Sarah; Vallely, Kat. - : Routledge - Taylor & Francis Group, 2021 BASE Show details 56 Conducting thematic analysis on brief texts: The structured tabular approach Robinson, Oliver. - : American Psychological Association, 2021 BASE Show details 57 Indicatives, subjunctives, and the falsity of the antecedent Skovgaard-Olsen, Niels; Collins, Peter. - : Wiley, 2021 BASE Show details 58 Super-recognisers: some people excel at both face and voice recognition Jenkins, Ryan; Robertson, David; Davis, Josh P.. - : The Conversation Trust, 2021 BASE Show details 59 The part-whole effect in super-recognisers and typical-range-ability controls Belanova, Elena; Davis, Josh P.; Thompson, Trevor. - : Elsevier, 2021 BASE Show details 60 The ‘comparative logic’ and why we need to explain interlanguage grammars Dominguez, Laura; Arche, Maria J. - : Frontiers Media S.A., 2021 BASE Show details Page: 1 2 3 4 5 6 7...70

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