Identifying the polarity of a text given the emotion of its author

The rise of digital communication systems provides an almost infinite source of information that can be useful to feed classification algorithms, so it makes use of an already categorized collection of opinions of the social network Twitter for the formation and generation of a model of classification of short texts; which aims to categorize the emotional tone found in an author’s Spanish-language digital text. In addition, linguistic, lexicographic and opinion mining computational tools are used to implement a series of methods that allow to automatically finding coincidences or orientations that allow determining the polarity of sentences and categorize them as positive, negative or neutral considering their lemmas. The results obtained from the analysis of emotions and polarity of this project, on the test phrases allow to observe a direct relationship between the categorized emotional tone and it is positive, negative or neutral classification, which allows to provide additional information to know the intention that the author had when he created the sentence. Determining these characteristics can be useful as a consistent information objective that can be leveraged by sectors where the prevalence of a product or service depends on user opinion, product rating or turns with satisfaction metrics.

Achieving Semantic Consistency for Multilingual Sentence Representation Using an Explainable Machine Natural Language Parser (MParser)

In multilingual semantic representation, the interaction between humans and computers faces the challenge of understanding meaning or semantics, which causes ambiguity and inconsistency in heterogeneous information. This paper proposes a Machine Natural Language Parser (MParser) to address the semantic interoperability problem between users and computers. By leveraging a semantic input method for sharing common atomic concepts, MParser represents any simple English sentence as a bag of unique and universal concepts via case grammar of an explainable machine natural language. In addition, it provides a human and computer-readable and -understandable interaction concept to resolve the semantic shift problems and guarantees consistent information understanding among heterogeneous sentence-level contexts. To evaluate the annotator agreement of MParser outputs that generates a list of English sentences under a common multilingual word sense, three expert participants manually and semantically annotated 75 sentences (505 words in total) in English. In addition, 154 non-expert participants evaluated the sentences’ semantic expressiveness. The evaluation results demonstrate that the proposed MParser shows higher compatibility with human intuitions.

Effect of COVID-19 on vaccination coverage in Brazil

During the COVID-19 pandemic, recommendations for maintaining physical distance, restricted mobility measures, as well as fear of mass transmission by going to health centers have significantly contributed to the general vaccination coverage, which by and large is decreasing worldwide; thus, favoring the potential re-emergence of vaccine-preventable diseases. In this study, we have used the existing data on vaccination coverage during the pre-pandemic (2019) as well as the pandemic (2020) period to evaluate the impact of coronavirus outbreaks during the vaccination drive in Brazil. Furthermore, we have accumulated data since 2015 among the different regions of the country to acquire more consistent information. The various vaccines analyzed in our study were meningococcal C conjugate, Triple antigen vaccine, 10-valent pneumococcal conjugate, and BCG; subsequently, the data were obtained from the National Disease Notification System. This study revealed that the ongoing immunization drive saw a steep decline of around 10 to 20% during the (2019–2020) pandemic period in Brazil. These results provide strong evidence towards the decreasing trends following the vaccination programs during the COVID-19 pandemic period in Brazil. Furthermore, our results also highlight the importance of adopting widespread multi-component interventions to improve vaccination uptake rates.

Selective exposure to COVID-19 vaccination information: the influence of prior attitude, perceived threat level and information limit

PurposeThe massive amount of available information and functionality of the Internet makes selective information seeking effortless. This paper aims to understand the selective exposure to information during a health decision-making task.Design/methodology/approachThis study conducted an experiment with a sample of 36 students to examine the influence of prior attitude, perceived threat level and information limit on users’ selective exposure to and recall of coronavirus disease 2019 (COVID-19) vaccination information. Participants were assigned to two conditions with or without an upper limit of the number of articles to be examined, and this study collected the number of articles read, the number of articles included in the report and recall score of the articles after one day of the experiment.FindingsThis study found that (1) participants with a negative attitude were more inclined to view attitude-consistent information and recalled attitude-consistent information more accurately, while participants with a positive attitude viewed more balanced information; (2) participants perceiving higher health threat level recalled attitude-consistent information more accurately; and (3) an upper limit on the number of articles to be viewed does not have any impact on selective exposure.Research limitations/implicationsThe findings of this paper pinpoint the disparity of influence of positive and negative attitudes on selective exposure to and selective recall of health information, which was not previously recognized.Practical implicationsVaccination campaigns should focus on reaching people with negative attitudes who are more prone to selective exposure to encourage them to seek more balanced information.Originality/valueThis is the first paper to explore selective exposure to COVID-19 vaccination information. This study found that people with a negative attitude and a higher level of perceived health threat are more prone to selective exposure, which was not found in previous research.

An analysis of the effectiveness of bankruptcy prediction models – an industry approach

Research background: Bankruptcy prediction models are frequently used in research. However, an industry approach is not often carried out. Due to this, this study included trends observable between the number of bankruptcies and its prediction by models. Purpose: The aim of the paper is to verify if changes in the number of actual bankruptcy in individual industries are properly predicted by the models. Also, if analyzed models are providing consistent information according to the risk of bankruptcy between industries. Research methodology: The data were collected from the Orbis database and the Coface reports. The period included in the study is 2014–2019. 5 Polish bankruptcy prediction models were used: these by D. Hadasik, E. Mączyńska and M. Zawadzki, M. Pogodzińska and S. Sojak, D. Wierzba and the Poznan one. Results: The analyzed models do not properly predict changes in the number of bankruptcy in individual industries, however, 3 out of 5 correctly predicted the trend for the entire sample. Analyzed models often provide inconsistent information. Hence, it seems sensible to use more than a few models in any further analyzes. Novelty: In the literature of the subject, there are often carried out analyses focused on the effectiveness of bankruptcy prediction models regarding individual companies. This research is focused on the prediction of changes in the number of companies to be considered as at bankruptcy risk between industries, and also on comparing these models.

Strategies for the survival of the Gusti School during 1939-1948

This article presents and analyzes the survival strategies of the Gusti School during 1939-1948. The specialized literature includes consistent information about the Gusti School, the monographs and research carried out, the School’s publications and the institutions in which the members of the Gusti School have been active. However, this article points out the important moments of the gustist activity after 1939, as forms of survival, through the documentary analysis of the texts published at that time, the documents of the Romanian Academy, as well as the subsequent sociological materials. An important part of the actions that indicate a certain type of strategy were extracted: journalism, the insistence to increase the sociological activity, even in conditions of war or the work carried out in different administrative positions. How was the activity of the Gusti School viewed after 1939 and what were the survival strategies? What were the main methods and strategies for promoting the Gusti School? In what (emergency) formula did the student teams continue their work? Is it possible to research in a time of war? Answering all these questions, we conclude that during 1939-1948, despite oppressive actions and purges targeting the Gusti School, its representatives managed to impose themselves, continuing the work to the limit allowed by the given political situations.

Addressing the transition to a chronic condition: exploring independent adoption of self-management by patients with ANCA-associated vasculitis

Objective Improvements in care have led to the recognition of Anti-neutrophil cytoplasm antibody associated vasculitis (AAV) as a chronic condition yet the self-management strategies considered a critical component of the care model for patients with more prevalent chronic conditions are yet to be formally integrated into the treatment of AAV patients. The work we present here aims to identify those self-management processes and tasks already being adopted by patients with AAV to help inform existing care and the development of a structured self-management programme. Methods We conducted a series of focus groups and semi-structured interviews with AAV patients collating the data and performing a post-hoc deductive analysis based on a consolidated framework of self-management processes. Results Despite the unique attributes and demands of AAV, patients adopted self-management behaviours previously identified and supported in patients with more prevalent chronic diseases. They proactively accessed information on their disease and learnt to mitigate their symptoms and side effects; they pursued a range of health promotion activities and accessed support from their social network and beyond and ultimately learnt to integrate the condition into their everyday life. Conclusions Our work has highlighted some key areas of self-management that might be usefully and immediately addressed including the provision of more consistent information relating to evolving symptoms and side-effects, additional support in accessing both appropriate care and community-based resources and the use of interventions to bolster resilience. Our findings will inform the development of tailored self-management programme but meantime provide a more contemporary context for current clinician-patient conversations.

Multimodal and Multiview Wound Monitoring with Mobile Devices

Along with geometric and color indicators, thermography is another valuable source of information for wound monitoring. The interaction of geometry with thermography can provide predictive indicators of wound evolution; however, existing processes are focused on the use of high-cost devices with a static configuration, which restricts the scanning of large surfaces. In this study, we propose the use of commercial devices, such as mobile devices and portable thermography, to integrate information from different wavelengths onto the surface of a 3D model. A handheld acquisition is proposed in which color images are used to create a 3D model by using Structure from Motion (SfM), and thermography is incorporated into the 3D surface through a pose estimation refinement based on optimizing the temperature correlation between multiple views. Thermal and color 3D models were successfully created for six patients with multiple views from a low-cost commercial device. The results show the successful application of the proposed methodology where thermal mapping on 3D models is not limited in the scanning area and can provide consistent information between multiple thermal camera views. Further work will focus on studying the quantitative metrics obtained by the multi-view 3D models created with the proposed methodology.

Perceiving Immigrants as a Threat: A Motivational Approach to False Consensus

False consensus, or biased projection of one’s opinion onto others, has repeatedly been described by political communication scholars as a derivative of selective exposure to attitude-consistent information. This study proposes a distinctive approach to understanding the phenomenon by suggesting “perceived threat” as a motivational factor that contributes to self-serving estimates of public opinion. Based on a nationally representative sample of U.S. adults, we test a path model in which political ideology relates to false consensus regarding the issue of immigration through cognitive assessments of communication environment and perceived immigration threat. Results suggest that the relationship between cognition and false consensus may not be direct but instead works through motivational factors when one perceives threat, and that conservatives are more sensitive to outgroup threat and thus are more likely to overestimate public consensus for their attitudes on immigration than their ideological counterparts. Implications of these findings are discussed.