This page has only limited features, please log in for full access.
The Coronavirus Disease 2019 (COVID-19) pandemic is transforming the world we live in, revealing our health, economic, and social weaknesses. In the local economy, the loss of job opportunities, the uncertainty about the future of small and medium-sized companies and the difficulties of families to face the effects of this crisis, invite us to investigate the perception of the local community. Based on a questionnaire applied to 313 citizens and 51 companies, this study explored the perception of these actors on the effects of the pandemic at the local level and determined the main factors that influenced their assessment using a multinomial logistic regression model. The results indicated a systematic concern for issues of employment, job security, and household debt. The variables of age and sex were significant when analyzing the vulnerability of certain groups, especially women and the elderly, to face the effects of the crisis and their role as citizens. At the business level, the focus was on economic policies that support its operational continuity and management capacity to face a changing scenario.
Benito Umaña-Hermosilla; Hanns De La Fuente-Mella; Claudio Elórtegui-Gómez; Marisela Fonseca-Fuentes. Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile. Sustainability 2020, 12, 9553 .
AMA StyleBenito Umaña-Hermosilla, Hanns De La Fuente-Mella, Claudio Elórtegui-Gómez, Marisela Fonseca-Fuentes. Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile. Sustainability. 2020; 12 (22):9553.
Chicago/Turabian StyleBenito Umaña-Hermosilla; Hanns De La Fuente-Mella; Claudio Elórtegui-Gómez; Marisela Fonseca-Fuentes. 2020. "Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile." Sustainability 12, no. 22: 9553.
This study focuses on identifying personality traits in computer science students and determining whether they are related to academic performance. In addition, the importance of the personality traits based on motivation scale and depression, anxiety, and stress scales were measured. A sample of 188 students from the Computer Engineering Schools of the Pontifical Catholic University of Valparaíso was used. Through econometric two-stage least squares and paired sample correlation analysis, the results obtained indicate that there is a relation between academic performance and the personality traits measured by educational motivation scale and the ranking of university entrance and gender. In addition, these results led to characterization of students based on their personality traits and provided elements that may enhance the development of an effective personality that allows students to successfully face their environment, playing an important role in the educational process.
Hanns De La Fuente-Mella; Claudia Guzmán Gutiérrez; Kathleen Crawford; Giancarla Foschino; Broderick Crawford; Ricardo Soto; Claudio León De La Barra; Felipe Cisternas Caneo; Eric Monfroy; Marcelo Becerra-Rozas; Claudio Elórtegui-Gómez. Analysis and Prediction of Engineering Student Behavior and Their Relation to Academic Performance Using Data Analytics Techniques. Applied Sciences 2020, 10, 7114 .
AMA StyleHanns De La Fuente-Mella, Claudia Guzmán Gutiérrez, Kathleen Crawford, Giancarla Foschino, Broderick Crawford, Ricardo Soto, Claudio León De La Barra, Felipe Cisternas Caneo, Eric Monfroy, Marcelo Becerra-Rozas, Claudio Elórtegui-Gómez. Analysis and Prediction of Engineering Student Behavior and Their Relation to Academic Performance Using Data Analytics Techniques. Applied Sciences. 2020; 10 (20):7114.
Chicago/Turabian StyleHanns De La Fuente-Mella; Claudia Guzmán Gutiérrez; Kathleen Crawford; Giancarla Foschino; Broderick Crawford; Ricardo Soto; Claudio León De La Barra; Felipe Cisternas Caneo; Eric Monfroy; Marcelo Becerra-Rozas; Claudio Elórtegui-Gómez. 2020. "Analysis and Prediction of Engineering Student Behavior and Their Relation to Academic Performance Using Data Analytics Techniques." Applied Sciences 10, no. 20: 7114.
The year 2017 was an intense electoral year in Chile, both parliamentary and presidential. In this context, by using computer intelligence, an interdisciplinary team conducted a collection and volumetric analysis of over 3 million Twitter messages belonging to users that mentioned, at least once, any of the presidential candidates, both in the first and second voting round. Our goal was focused on analyzing the relationship between traditional media (radio and television) and Twitter, probing user interactions during the broadcast of live political shows, with emphasis on presidential debates. For this purpose, we carried out a volumetric analysis of all mentions in social media during the broadcast of live political shows to characterize the digital attention of the audience, under different parameters. Our results show that there is high user interest in the digital debate regarding presidential debates, a positive correlation between traditional media and Twitter during the broadcast of live political shows, and that, also, the latter trigger social media; furthermore, we verify the double screen phenomenon made possible by mobile platforms.
Pedro Santander; Claudio Elórtegui; Camila Buzzo. Twitter, Presidential Debates and Attention Economy: A Symbiosis between Television Audience and Social Media Users during Campaign Season. Communication & Society 2020, 33, 51 -65.
AMA StylePedro Santander, Claudio Elórtegui, Camila Buzzo. Twitter, Presidential Debates and Attention Economy: A Symbiosis between Television Audience and Social Media Users during Campaign Season. Communication & Society. 2020; 33 (3):51-65.
Chicago/Turabian StylePedro Santander; Claudio Elórtegui; Camila Buzzo. 2020. "Twitter, Presidential Debates and Attention Economy: A Symbiosis between Television Audience and Social Media Users during Campaign Season." Communication & Society 33, no. 3: 51-65.
The impact of computational technologies and the worldwide use of Internet entails a theoretical and methodological challenge for social scientists, considering the purpose of observing, interpreting and explaining human and social behaviour. Today, the digital environment seems to be an adequate space for this exploration and the emergence of the Web 2.0 offers common people the possibility of expressing and sharing their opinions on a daily basis. Due to the ubiquity of technology, Internet and social media in people’s lives, socialization and its expressiveness have changed. If this is the case, the means to measure the perceptions, opinions and judgements of citizens should also change. The immense quantity of data available to be analysed today poses a challenge for the traditional scientific model. In this sense, it could be necessary for social research to move towards the analysis of the web and consider the potential predictive capacity of digital demoscopy. A new field of study has opened, with interest in exploring the predictive capacity of social media in electoral contexts. As a research group comprised by linguists, communication experts and engineers we explored the predictive potential of social media in three national elections that took place in Chile during 2017. Our objective was to explore a methodological design that allows predicting the result of political elections through the use of inductive algorithms and the automatic processing of messages with political opinion in social media. Through computational intelligence, we were able to follow, collect and analyse millions of tweets, and to improve our forecast each time. Our learning based on empirical research was fundamental to improve our procedures and to refine our variables and, thus, improve our prediction.
Pedro Santander; Rodrigo Alfaro; Héctor Allende-Cid; Claudio Elórtegui; Cristian González. Analyzing social media, analyzing the social? A methodological discussion about the demoscopic and predictive potential of social media. Quality & Quantity 2020, 54, 903 -923.
AMA StylePedro Santander, Rodrigo Alfaro, Héctor Allende-Cid, Claudio Elórtegui, Cristian González. Analyzing social media, analyzing the social? A methodological discussion about the demoscopic and predictive potential of social media. Quality & Quantity. 2020; 54 (3):903-923.
Chicago/Turabian StylePedro Santander; Rodrigo Alfaro; Héctor Allende-Cid; Claudio Elórtegui; Cristian González. 2020. "Analyzing social media, analyzing the social? A methodological discussion about the demoscopic and predictive potential of social media." Quality & Quantity 54, no. 3: 903-923.