Character N-Grams for Detecting Deceptive Controversial Opinions

[EN] Controversial topics are present in the everyday life, and opinions about them can be either truthful or deceptive. Deceptive opinions are emitted to mislead other people in order to gain some advantage. In the most of the cases humans cannot detect whether the opinion is deceptive or truthful, however, computational approaches have been used successfully for this purpose. In this work, we evaluate a representation based on character n-grams features for detecting deceptive opinions. We consider opinions on the following: abortion, death penalty and personal feelings about the best friend; three domains studied in the state of the art. We found character n-grams effective for detecting deception in these controversial domains, even more than using psycholinguistic features. Our results indicate that this representation is able to capture relevant information about style and content useful for this task. This fact allows us to conclude that the proposed one is a competitive text representation with a good trade-off between simplicity and performance.We would like to thank CONACyT for partially supporting this work under grants 613411, CB-2015-01-257383, and FC-2016/2410. The work of the last author was partially funded by the Spanish MINECO under the research project SomEMBED (TIN2015-71147-C2-1-P).Sánchez-Junquera, JJ.; Luis Villaseñor Pineda; Montes Gomez, M.; Rosso, P. (2018). Character N-Grams for Detecting Deceptive Controversial Opinions. Lecture Notes in Computer Science. 11018:135-140. https://doi.org/10.1007/978-3-319-98932-7_13S13514011018Aritsugi, M., et al.: Combining word and character n-grams for detecting deceptive opinions, vol. 1, pp. 828–833. IEEE (2017)Buller, D.B., Burgoon, J.K.: Interpersonal deception theory. Commun. Theory 6(3), 203–242 (1996)Cagnina, L.C., Rosso, P.: Detecting deceptive opinions: intra and cross-domain classification using an efficient representation. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 25(Suppl. 2), 151–174 (2017)Feng, S., Banerjee, R., Choi, Y.: Syntactic stylometry for deception detection, pp. 171–175. Association for Computational Linguistics (2012)Fusilier, D.H., Montes-y-Gómez, M., Rosso, P., Cabrera, R.G.: Detection of opinion spam with character n-grams. In: Gelbukh, A. (ed.) CICLing 2015. LNCS, vol. 9042, pp. 285–294. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-18117-2_21Hernández-Castañeda, Á., Calvo, H., Gelbukh, A., Flores, J.J.G.: Cross-domain deception detection using support vector networks. Soft Comput. 21(3), 1–11 (2016)Mihalcea, R., Strapparava, C.: The lie detector: explorations in the automatic recognition of deceptive language. In: Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pp. 309–312. Association for Computational Linguistics (2009)Ott, M., Choi, Y., Cardie, C., Hancock, J.T.: Finding deceptive opinion spam by any stretch of the imagination. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1, pp. 309–319. Association for Computational Linguistics (2011)Pérez-Rosas, V., Mihalcea, R.: Cross-cultural deception detection. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), vol. 2, pp. 440–445 (2014)Sapkota, U., Solorio, T., Montes-y-Gómez, M., Bethard, S.: Not all character n-grams are created equal: a study in authorship attribution. In: Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 93–102 (2015)Vrij, A.: Detecting Lies and Deceit: Pitfalls and Opportunities. Wiley, Hoboken (2008

On the primordial scenario for abundance variations within globular clusters. The isochrone test

Self-enrichment processes occurring in the early stages of a globular cluster lifetime are generally invoked to explain the observed CNONaMgAl abundance anticorrelations within individual Galactic globulars.We have tested, with fully consistent stellar evolution calculations, if theoretical isochrones for stars born with the observed abundance anticorrelations satisfy the observational evidence that objects with different degrees of these anomalies lie on essentially identical sequences in the Color-Magnitude-Diagram (CMD). To this purpose, we have computed for the first time low-mass stellar models and isochrones with an initial metal mixture that includes the extreme values of the observed abundance anticorrelations, and varying initial He mass fractions. Comparisons with 'normal' alpha-enhanced isochrones and suitable Monte Carlo simulations that include photometric errors show that a significant broadening of the CMD sequences occurs only if the helium enhancement is extremely large (in this study, when Y=0.35) in the stars showing anomalous abundances. Stellar luminosity functions up to the Red Giant Branch tip are also very weakly affected, apart from - depending on the He content of the polluting material - the Red Giant Branch bump region. We also study the distribution of stars along the Zero Age Horizontal Branch, and derive general constraints on the relative location of objects with and without abundance anomalies along the observed horizontal branches of globular clusters.Comment: Accepted for publication in Ap

Work factors and psychological distress in nurses' aides: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Nurses' aides (assistant nurses), the main providers of practical patient care in many countries, are doing both emotional and heavy physical work, and are exposed to frequent social encounters in their job. There is scarce knowledge, though, of how working conditions are related to psychological distress in this occupational group. The aim of this study was to identify work factors that predict the level of psychological distress in nurses' aides.</p> <p>Methods</p> <p>The sample of this prospective study comprised 5076 Norwegian nurses' aides, not on leave when they completed a mailed questionnaire in 1999. Of these, 4076 (80.3 %) completed a second questionnaire 15 months later. A wide spectrum of physical, psychological, social, and organisational work factors were measured at baseline. Psychological distress (anxiety and depression) was assessed at baseline and follow-up by the SCL-5, a short version of Hopkins Symptom Checklist-25.</p> <p>Results</p> <p>In a linear regression model of the level of psychological distress at follow-up, with baseline level of psychological distress, work factors, and background factors as independent variables, work factors explained 2 % and baseline psychological distress explained 34 % of the variance. Exposures to role conflicts, exposures to threats and violence, working in apartment units for the aged, and changes in the work situation between baseline and follow-up that were reported to result in less support and encouragement were positively associated with the level of psychological distress. Working in psychiatric departments, and changes in the work situation between baseline and follow-up that gave lower work pace were negatively associated with psychological distress.</p> <p>Conclusion</p> <p>The study suggests that work factors explain only a modest part of the psychological distress in nurses' aides. Exposures to role conflicts and threats and violence at work may contribute to psychological distress in nurses' aides. It is important that protective measures against violent patients are implemented, and that occupational health officers offer victims of violence appropriate support or therapy. It is also important that health service organisations focus on reducing role conflicts, and that leaders listen to and consider the views of the staff.</p

Factors influencing students’ intention to use internet for academic purposes

This study aimed to investigate the factors influencing students’ intention to use the Internet for academic purposes amongst 204 final year business students in public universities in Malaysia.This study integrated theory of planned behavior (TPB) and theory of acceptance model (TAM) as the base model toward that purpose.The research model employs the variables from both theories namely attitudes, subjective norms, perceived behavioral control, perceived usefulness, perceived ease of use, intention, and behavior.A multiple regression analysis provides empirical support for the applicability of integration of TPB and TAM in predicting students’ intention to use the Internet for academic purposes.Results of the study show that attitudes, perceived behavioral control, and perceived usefulness are statistically significant in influencing intention to use the Internet for academic purposes.Based on the results, it can be concluded that students’ intention to use the Internet for academic purposes could be predicted from their attitudes, perceived behavioral control, and perceived usefulness at 49% level.In view of the results, several implications and recommendations are discussed

A preliminary analysis of interactive effects between common classroom contingencies and methylphenidate.

To assess the drug-behavior interaction effects with an 8-year-old boy wih attention deficit hyperactivity disorder, common classroom antecedent (e.g., seating arrangement) and consequent (e.g., peer prompts) stimuli were alternated within a school day while drug conditions (methylphenidate vs. placebo) were alternated across days. The results suggested that peer attention maintained disruptive behavior when methylphenidate was absent but not when it was present

Multiple criteria fake reviews detection using belief function theory

International audienceChecking online reviews before making a purchase becomes a permanent habit. Hence, online consumer reviews, product and services play an increasingly spreading role in consumer purchasing decisions. Unfortunately, the importance of advertising and the attraction of profit have led to the appearance of fake reviews in order to mislead readers. Considering that the reviews are generally imperfect, the spam reviews detection becomes one of the most important problems. To tackle this problem, we propose a new method of multi-criteria fake reviews under belief function theory. This approach treats the uncertainty in the rating reviewers' given to multiple evaluation criteria, takes into account the similarity between all provided reviews and deals with missing data. We evaluate our method through artificial datasets. Then, we use a real dataset to validate it. The results prove that the proposed approach is a useful solution for the fake reviews detection problem