Combining granularity-based topic-dependent and topic-independent evidences for opinion detection

Fouille des opinion, une sous-discipline dans la recherche d'information (IR) et la linguistique computationnelle, fait référence aux techniques de calcul pour l'extraction, la classification, la compréhension et l'évaluation des opinions exprimées par diverses sources de nouvelles en ligne, social commentaires des médias, et tout autre contenu généré par l'utilisateur. Il est également connu par de nombreux autres termes comme trouver l'opinion, la détection d'opinion, l'analyse des sentiments, la classification sentiment, de détection de polarité, etc. Définition dans le contexte plus spécifique et plus simple, fouille des opinion est la tâche de récupération des opinions contre son besoin aussi exprimé par l'utilisateur sous la forme d'une requête. Il y a de nombreux problèmes et défis liés à l'activité fouille des opinion. Dans cette thèse, nous nous concentrons sur quelques problèmes d'analyse d'opinion. L'un des défis majeurs de fouille des opinion est de trouver des opinions concernant spécifiquement le sujet donné (requête). Un document peut contenir des informations sur de nombreux sujets à la fois et il est possible qu'elle contienne opiniâtre texte sur chacun des sujet ou sur seulement quelques-uns. Par conséquent, il devient très important de choisir les segments du document pertinentes à sujet avec leurs opinions correspondantes. Nous abordons ce problème sur deux niveaux de granularité, des phrases et des passages. Dans notre première approche de niveau de phrase, nous utilisons des relations sémantiques de WordNet pour trouver cette association entre sujet et opinion. Dans notre deuxième approche pour le niveau de passage, nous utilisons plus robuste modèle de RI i.e. la language modèle de se concentrer sur ce problème. L'idée de base derrière les deux contributions pour l'association d'opinion-sujet est que si un document contient plus segments textuels (phrases ou passages) opiniâtre et pertinentes à sujet, il est plus opiniâtre qu'un document avec moins segments textuels opiniâtre et pertinentes. La plupart des approches d'apprentissage-machine basée à fouille des opinion sont dépendants du domaine i.e. leurs performances varient d'un domaine à d'autre. D'autre part, une approche indépendant de domaine ou un sujet est plus généralisée et peut maintenir son efficacité dans différents domaines. Cependant, les approches indépendant de domaine souffrent de mauvaises performances en général. C'est un grand défi dans le domaine de fouille des opinion à développer une approche qui est plus efficace et généralisé. Nos contributions de cette thèse incluent le développement d'une approche qui utilise de simples fonctions heuristiques pour trouver des documents opiniâtre. Fouille des opinion basée entité devient très populaire parmi les chercheurs de la communauté IR. Il vise à identifier les entités pertinentes pour un sujet donné et d'en extraire les opinions qui leur sont associées à partir d'un ensemble de documents textuels. Toutefois, l'identification et la détermination de la pertinence des entités est déjà une tâche difficile. Nous proposons un système qui prend en compte à la fois l'information de l'article de nouvelles en cours ainsi que des articles antérieurs pertinents afin de détecter les entités les plus importantes dans les nouvelles actuelles. En plus de cela, nous présentons également notre cadre d'analyse d'opinion et tâches relieés. Ce cadre est basée sur les évidences contents et les évidences sociales de la blogosphère pour les tâches de trouver des opinions, de prévision et d'avis de classement multidimensionnel. Cette contribution d'prématurée pose les bases pour nos travaux futurs. L'évaluation de nos méthodes comprennent l'utilisation de TREC 2006 Blog collection et de TREC Novelty track 2004 collection. La plupart des évaluations ont été réalisées dans le cadre de TREC Blog track.Opinion mining is a sub-discipline within Information Retrieval (IR) and Computational Linguistics. It refers to the computational techniques for extracting, classifying, understanding, and assessing the opinions expressed in various online sources like news articles, social media comments, and other user-generated content. It is also known by many other terms like opinion finding, opinion detection, sentiment analysis, sentiment classification, polarity detection, etc. Defining in more specific and simpler context, opinion mining is the task of retrieving opinions on an issue as expressed by the user in the form of a query. There are many problems and challenges associated with the field of opinion mining. In this thesis, we focus on some major problems of opinion mining

Effectiveness gain of polarity detection through topic domains

National audienceMost of the work on polarity detection consists in finding out negative or positive words in a document using sentiment lexical resources. Indeed, some versions of such approaches have performed well but most of these approaches rely only on prior polarity of words and do not exploit the contextual polarity of words. Sentiment semantics of a term vary from one domain to another. For example, the word "unpredictable" conveys a positive feeling about a movie plot, but the same word conveys negative feeling in context of operating of a digital camera. In this work, we demonstrate this aspect of sentiment polarity. We use TREC Blog 2006 Data collection with topics of TREC Blog 2006 and 2007 for experimentation. The results of our experiments showed an improvement (95%) on polarity detection. The conclusion is that the context plays a role on the polarity of each word

Exploring hospital inpatients’ awareness of their falls risk : a qualitative exploratory study

Patient falls in hospital may lead to physical, psychological, social and financial impacts. Understanding patients’ perceptions of their fall risk will help to direct fall prevention strategies and understand patient behaviours. The aim of this study was to explore the perceptions and experiences that influence a patient’s understanding of their fall risk in regional Australian hospitals. Semi-structured, individual interviews were conducted in wards across three Australian hospitals. Participants were aged 40 years and over, able to communicate in English and were mobile prior to hospital admission. Participants were excluded from the study if they returned a Standardised Mini-Mental State Examination (SMMSE) score of less than 18 when assessed by the researcher. A total of 18 participants with an average age of 69.8 years (SD ± 12.7, range 41 to 84 years) from three regional Victorian hospitals were interviewed for this study. Data were analysed using a reflexive thematic analysis identifying three major themes; (1) Environment (extrinsic) (2) Individual (intrinsic), and (3) Outcomes, as well as eight minor themes. Participants recognised the hazardous nature of a hospital and their personal responsibilities in staying safe. Falls education needs to be consistently delivered, with the focus on empowering the patient to help them adjust to changes in their clinical condition, whether temporary or permanent. © 2022 by the authors

Adult inpatients’ perceptions of their fall risk : a scoping review

Patient falls in hospitals continue to be a global concern due to the poor health outcomes and costs that can occur. A large number of falls in hospitals are unwitnessed and mostly occur due to patient behaviours and not seeking assistance. Understanding these patient behaviours may help to direct fall prevention strategies, with evidence suggesting the need to integrate patients’ perspectives into fall management. The aim of this scoping review was to explore the extent of the literature about patients’ perceptions and experiences of their fall risk in hospital and/or of falling in hospital. This review was conducted using a five-stage methodological framework recommended by Arksey and O’Malley. A total of nine databases were searched using key search terms such as “fall*”, “perception” and “hospital.” International peer-reviewed and grey literature were searched between the years 2011 and 2021. A total of 41 articles, ranging in study design, met the inclusion criteria. After reporting on the article demographics and fall perception constructs and measures, the qualitative and quantitative findings were organised into five domains: Fall Risk Perception Measures, Patients’ Perceptions of Fall Risk, Patients’ Perceptions of Falling in Hospital, Patients’ Fear of Falling and Barriers to Fall Prevention in Hospital. Approximately two-thirds of study participants did not accurately identify their fall risk compared to that defined by a health professional. This demonstrates the importance of partnering with patients and obtaining their insights on their perceived fall risk, as this may help to inform fall management and care. This review identified further areas for research that may help to inform fall prevention in a hospital setting, including the need for further research into fall risk perception measures. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Evaluating the effects of a therapeutic day rehabilitation program and inclusion of gardening in an Australian rural community health service

Therapeutic day rehabilitation (TDR) is a non-residential intensive structured program designed for individuals recovering from substance misuse. A weekly afternoon of therapeutic gardening was a new incentive initiated in a TDR program at one Australian community health service, designed to give participants the opportunity to spend time outdoors connecting with nature and each other. The aim of this study was to explore perceptions of participants enrolled in this program by employing a convergent parallel mixed-method design using qualitative individual, semi-structured interviews (n = 14) and longitudinal quantitative quality of life (QOL) data at three different intervals (n = 17). The analysis of the quantitative data showed that there was a statistically significant increase in the participants' QOL scores in three of four domains (physical health, psychological, social relationships) when comparing baseline and post completion of the TDR. These observed changes were maintained at the 4-week follow up. The key findings from the semi-structured interviews include positive effects for participants on social connectivity, structure and achievement, understanding of recovery and relaxation from contact with nature. This study shows that a combination of TDR and therapeutic gardening can improve participants' physical health, psychological health and social relationships. © 2021 La Trobe University