Models of unexplained symptoms associated with occupational and environmental exposures.

Unexplained illnesses characterized by nonspecific, multisystem complaints are often attributed to occupational or environmental chemical exposures. This raises difficulties for the regulatory authorities, who are frequently unable to agree on the existence, nature, or source of such illnesses. It is proposed that many of these difficulties derive from an adherence to a traditional medical model of disease and that the application of a biopsychosocial approach would be more effective for both research and individual case management. A number of models derived from the field of health psychology are discussed in terms of their application to occupational and environmental syndromes. A specific example is described that relates to the health problems experienced by sheep farmers in the United Kingdom who are exposed to organophosphate-based pesticides. The source of their complaints and the responses of the health professionals and the regulatory authorities are discussed within the context of a biopsychosocial approach that focuses on illness rather than on organic disease as the unit of study and explores the interaction between the various physical and psychosocial variables involved. It is proposed that this approach, which is already well established in the fields of human and social sciences, should be adopted more readily by those concerned with occupational and environmental epidemiology

The Digital Flynn Effect: Complexity of Posts on Social Media Increases over Time

Parents and teachers often express concern about the extensive use of social media by youngsters. Some of them see emoticons, undecipherable initialisms and loose grammar typical for social media as evidence of language degradation. In this paper, we use a simple measure of text complexity to investigate how the complexity of public posts on a popular social networking site changes over time. We analyze a unique dataset that contains texts posted by 942, 336 users from a large European city across nine years. We show that the chosen complexity measure is correlated with the academic performance of users: users from high-performing schools produce more complex texts than users from low-performing schools. We also find that complexity of posts increases with age. Finally, we demonstrate that overall language complexity of posts on the social networking site is constantly increasing. We call this phenomenon the digital Flynn effect. Our results may suggest that the worries about language degradation are not warranted

Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users

If people with high risk of suicide can be identified through social media like microblog, it is possible to implement an active intervention system to save their lives. Based on this motivation, the current study administered the Suicide Probability Scale(SPS) to 1041 weibo users at Sina Weibo, which is a leading microblog service provider in China. Two NLP (Natural Language Processing) methods, the Chinese edition of Linguistic Inquiry and Word Count (LIWC) lexicon and Latent Dirichlet Allocation (LDA), are used to extract linguistic features from the Sina Weibo data. We trained predicting models by machine learning algorithm based on these two types of features, to estimate suicide probability based on linguistic features. The experiment results indicate that LDA can find topics that relate to suicide probability, and improve the performance of prediction. Our study adds value in prediction of suicidal probability of social network users with their behaviors

Semantic Sentiment Analysis of Twitter Data

Internet and the proliferation of smart mobile devices have changed the way information is created, shared, and spreads, e.g., microblogs such as Twitter, weblogs such as LiveJournal, social networks such as Facebook, and instant messengers such as Skype and WhatsApp are now commonly used to share thoughts and opinions about anything in the surrounding world. This has resulted in the proliferation of social media content, thus creating new opportunities to study public opinion at a scale that was never possible before. Naturally, this abundance of data has quickly attracted business and research interest from various fields including marketing, political science, and social studies, among many others, which are interested in questions like these: Do people like the new Apple Watch? Do Americans support ObamaCare? How do Scottish feel about the Brexit? Answering these questions requires studying the sentiment of opinions people express in social media, which has given rise to the fast growth of the field of sentiment analysis in social media, with Twitter being especially popular for research due to its scale, representativeness, variety of topics discussed, as well as ease of public access to its messages. Here we present an overview of work on sentiment analysis on Twitter.Comment: Microblog sentiment analysis; Twitter opinion mining; In the Encyclopedia on Social Network Analysis and Mining (ESNAM), Second edition. 201

Arsonists or firefighters? Affectiveness in agile software development

In this paper, we present an analysis of more than 500K comments from open-source repositories of software systems developed using agile methodologies. Our aim is to empirically determine how developers interact with each other under certain psychological conditions generated by politeness, sentiment and emotion expressed within developers' comments. Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat, and tools such as issue tracking systems. The way in which they communicate a ects the development process and the productivity of the people involved in the project. We evaluated politeness, sentiment and emotions of comments posted by agile developers and studied the communication ow to understand how they interacted in the presence of impolite and negative comments (and vice versa). Our analysis shows that \ re ghters" prevail. When in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 13% and 25%, respectively; ANGER however, has a probability of 40% of being followed by a further ANGER comment. The result could help managers take control the development phases of a system, since social aspects can seriously a ect a developer's productivity. In a distributed agile environment this may have a particular resonance

Unhappiness and dissatisfaction in doctors cannot be predicted by selectors from medical school application forms: A prospective, longitudinal study

BACKGROUND: Personal statements and referees' reports are widely used on medical school application forms, particularly in the UK, to assess the suitability of candidates for a career in medicine. However there are few studies which assess the validity of such information for predicting unhappiness or dissatisfaction with a career in medicine. Here we combine data from a long-term prospective study of medical student selection and training, with an experimental approach in which a large number of assessors used a paired comparison technique to predict outcome. METHODS: Data from a large-scale prospective study of students applying to UK medical schools in 1990 were used to identify 40 pairs of doctors, matched by sex, for whom personal statements and referees' reports were available, and who in a 2002/3 follow-up study, one pair member was very satisfied and the other very dissatisfied with medicine as a career. In 2005, 96 assessors, who were experienced medical school selectors, doctors, medical students or psychology students, used information from the doctors' original applications to judge which member of each pair of doctors was the happier, more satisfied doctor. RESULTS: None of the groups of assessors were significantly different from chance expectations in using applicants' personal statements and the referees' reports to predict actual future satisfaction or dissatisfaction, the distribution being similar to binomial expectations. However judgements of pairs of application forms from pairs of doctors showed a non-binomial distribution, indicating consensus among assessors as to which doctor would be the happy doctor (although the consensus was wrong in half the cases). Assessors taking longer to do the task concurred more. Consensus judgements seem mainly to be based on referees' predictions of academic achievement (even though academic achievement is not actually a valid predictor of happiness or satisfaction). CONCLUSION: Although widely used in medical student selection to assess motivation, interest and commitment to a medical career, the personal statement and the referee's report cannot validly be used by assessors, including experienced medical school selectors, to identify doctors who will subsequently be dissatisfied with a medical career

In verbis, vinum? Relating themes in an open-ended writing task to alcohol behaviors

Alcohol's function as a regulator of emotions has long been denoted in figures of speech, most famously 'in vino, veritas' (in wine,truth). In contrast, we ask whether an individual's alcohol-related behaviors can be inferred from the words they use to write about alcohol. Participants completed an open-ended essay as part of a survey on alcohol attitudes and behaviors. We used a computerized technique, the Meaning Extraction Method, to summarize the responses into thematic tropes, and correlated these with quantitative measurements of demographics, attitudes and behaviors. Participants were recruited using a random population postal survey in the U.K (n=1229). Principal components analysis identified co-occurring words to locate themes in the responses. Seven themes were identified that corresponded to both negative and positive aspects of alcohol consumption ranging from concern for the influence of alcohol on others (e.g., children and family) to participants' own enjoyment of alcohol (e.g., social drinking). Significant correlations suggested a relationship between the essay responses and individual consumption patterns and attitudes. This study therefore examines how individuals in UK drinking cultures commonly construe alcohol consumption in their own words

Caring for Caregivers (C4C): study protocol for a pilot feasibility randomised control trial of Positive Written Disclosure for older adult caregivers of people with psychosis

Background: The caregivers of people who experience psychosis are themselves at risk of developing physical and mental health problems. This risk is increased for older adult caregivers who also have to manage the lifestyle and health changes associated with ageing. As a consequence, older adult caregivers are in particular need of support; we propose a Written Emotional Disclosure (WED) intervention, called Positive Written Disclosure (PWD). Methods/design: This is a pilot randomised controlled trial of PWD compared to a neutral writing control and a no writing condition. We aim to recruit 60 participants, 20 in each arm. This study will utilise a mixed-methods approach and collect quantitative (questionnaires) and qualitative (interviews) data. Quantitative data will be collected at baseline and 1, 3, and 6 months post baseline. Participants who complete a writing task (PWD or neutral writing control) will be invited to complete an exit interview to discuss their experiences of the intervention and study. The study is supported by a patient and public involvement group. Discussion: The results of this trial will determine whether a definitive trial is justified. If so, the quantitative and qualitative findings will be used to refine the intervention and study protocols

A Decade of Shared Tasks in Digital Text Forensics at PAN

[EN] Digital text forensics aims at examining the originality and credibility of information in electronic documents and, in this regard, to extract and analyze information about the authors of these documents. The research field has been substantially developed during the last decade. PAN is a series of shared tasks that started in 2009 and significantly contributed to attract the attention of the research community in well-defined digital text forensics tasks. Several benchmark datasets have been developed to assess the state-of-the-art performance in a wide range of tasks. In this paper, we present the evolution of both the examined tasks and the developed datasets during the last decade. We also briefly introduce the upcoming PAN 2019 shared tasks.We are indebted to many colleagues and friends who contributed greatly to PAN's tasks: Maik Anderka, Shlomo Argamon, Alberto Barrón-Cedeño, Fabio Celli, Fabio Crestani, Walter Daelemans, Andreas Eiselt, Tim Gollub, Parth Gupta, Matthias Hagen, Teresa Holfeld, Patrick Juola, Giacomo Inches, Mike Kestemont, Moshe Koppel, Manuel Montes-y-Gómez, Aurelio Lopez-Lopez, Francisco Rangel, Miguel Angel Sánchez-Pérez, Günther Specht, Michael Tschuggnall, and Ben Verhoeven. Our special thanks go to PAN¿s sponsors throughout the years and not least to the hundreds of participants.Potthast, M.; Rosso, P.; Stamatatos, E.; Stein, B. (2019). A Decade of Shared Tasks in Digital Text Forensics at PAN. Lecture Notes in Computer Science. 11438:291-300. https://doi.org/10.1007/978-3-030-15719-7_39S2913001143