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The purpose of this paper is to present an approach for forecasting mental health conditions and emotions of a given population during the COVID-19 pandemic in Argentina based on social media contents.

Mental health conditions and emotions are captured via markers, which link social media contents with lexicons. First, the authors build time series models that describe the evolution of markers and their correlation with crisis events. Second, the authors use the time series for forecasting markers and identifying high prevalence points for the estimated markers.

The authors evaluated different forecasting strategies that yielded different performance and capabilities. In the best scenario, high prevalence periods of emotions and mental health issues can be satisfactorily predicted with a neural network strategy, even at early stages of a crisis (e.g. a training period of seven days).

This work contributes to a better understanding of how psychological processes related to crises manifest in social media, and this is a valuable asset for the design, implementation and monitoring of health prevention and communication policies.

Although there have been previous efforts to predict mental states of individuals, the analysis of mental health at the collective level has received scarce attention. The authors take a step forward by proposing a forecasting approach for analyzing the mental health of a given population at a larger scale.

The objective of this article is to analyze fruit and vegetable (FV) purchasing decisions between 2011–12 and 2016–17 in Chile, and FV purchases by level of education in this period as determinant to explain dietary disparities across population groups.

Using Oaxaca-Blinder decomposition, the authors analyze FV purchases over time. Taking into consideration censoring, this study uses two waves of the Family Budget Survey (national representative) by the National Statistics Institute of Chile.

The authors find that when comparing income quintiles 1–4, between 2011–12 and 2016–17, the years of education of the household head cannot explain FV purchases disparities. In contrast, in income quintile 5, between 2011–12 and 2016–17, the marginal effect of education of the household head has significantly decreased FV purchases. When analyzing social determinants, gender and income quintiles in 2016–17, they do not have a significant effect on FV purchase disparities. However, the zone of the household, metropolitan zone vs other urban zones in the country has a significant effect on FV purchase disparities.

The datasets cover food home purchases.

The authors can conclude the relevance of implementing policies and programs to lead for healthier food environments such as offer more FVs in the school feeding program and social protection nutrition sensitive measures.

Using two waves of a nationally representative dataset, this article decomposes the effect of education of the household head to explain FV purchase disparities.

Recommender agents are used to make recommendations of interesting items in a wide variety of application domains, such as web page recommendation, music, e‐commerce, movie recommendation, tourism, restaurant recommendation, among others. Despite the various and different domains in which recommender agents are used and the variety of approaches they use to represent user interests and make recommendations, there is some functionality that is common to all of them, such as user model management and recommendation of interesting items. This paper aims at generalizing these common behaviors into a framework that enables developers to reuse recommender agents' main characteristics in their own developments.

This work presents a framework for recommendation that provides the control structures, the data structures and a set of algorithms and metrics for different recommendation methods. The proposed framework acts as the base design for recommender agents or applications that want to add the already modeled and implemented capabilities to their own functionality. In contrast with other proposals, this framework is designed to enable the integration of diverse user models, such as demographic, content‐based and item‐based. In addition to the different implementations provided for these components, new algorithms and user model representations can be easily added to the proposed approach. Thus, personal agents originally designed to assist a single user can reuse the behavior implemented in the framework to expand their recommendation strategies.

The paper describes three different recommender agents built by materializing the proposed framework: a movie recommender agent, a tourism recommender agent, and a web page recommender agent. Each agent uses a different recommendation approach. PersonalSearcher, an agent originally designed to suggest interesting web pages to a user, was extended to collaboratively assist a group of users using content‐based algorithms. MovieRecommender recommends interesting movies using an item‐based approach and Traveller suggests holiday packages using demographic user models. Findings encountered during the development of these agents and their empirical evaluation are described here.

The advantages of the proposed framework are twofold. On the one hand, the functionality provided by the framework enables the development of recommender agents without the need for implementing its whole set of capabilities from scratch. The main processes and data structures of recommender agents are already implemented. On the other hand, already existing agents can be enhanced by incorporating the functionality provided by the recommendation framework in order to act collaboratively.

The purpose of this work is to analyse the relationships between the personality traits of linked users in online social networks. First the authors tried to discover relation patterns between personality dimensions in conversations. They also wanted to verify some hypotheses: whether users' personality is stable throughout different conversation threads and whether the similarity-attraction paradigm can be verified in this context. They used the five factor model of personality or Big Five, which has been widely studied in psychology.

One of the approaches to detect users' personalities is by analysing the language they use when they talk to others. Based on this assumption the authors computed users' personality from the conversations extracted from the MySpace social network. Then the authors analysed the relationships among personality traits of users to discover patterns.

The authors found that there are patterns between some personality dimensions in conversation threads, for example, agreeable people tend to communicate with extroverted people. They confirmed that the personality stability theory can be verified in social networks. Finally the authors could verify the similarity-attraction paradigm for some values of personality traits, such as extroversion, agreeableness, and openness to experience.

The results the authors found provide some clues about how people communicate within online social networks, particularly who they tend to communicate with depending on their personality. The discovered patterns can be used in a wide range of applications, such as suggesting contacts in online social networks. Although some studies have been made regarding the role of personality in social media, no similar analysis has been done to evaluate how users communicate in social media considering their personality.

Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. Those systems mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, the purpose of this paper is to shed some light on the impact of personality traits on followee selection.

The authors performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. The authors analysed three different similarity measures. First, the authors computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, the authors computed the dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, the authors computed a cross-dimension similarity considering each personality dimension in relation to the others.

This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity might not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated.

This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.

The purpose of this paper is to analyze the innovation process of organizations representing the main sectors of Brazilian economic activity.

The literature review focuses on analyzing the innovation process characteristics regarding the innovation types. The authors carried out interviews with executives and managers in charge of innovation at the leading large companies in the respective sectors analyzed. The data analysis of this qualitative research was structured in three steps. The first step is the analysis of data collected for encoding, the second step, the summarization of the common points presented by the companies in each sector and, finally, the interpretation of these data, aided by triangulation from secondary data that support the analysis of the collected primary data.

The main contribution of this study is to characterize the innovation process of organizations representing the main sectors of the Brazilian economy, with a classification regarding the sectoral innovation standard.

The authors’ intent is that the paper can contribute with a comparative analysis among companies of the same sector and, subsequently, among companies of the different surveyed sectors. Thus, the characterization aims to present the companies’ innovation process and the comparative analysis aims to verify the innovation sectoral patterns. In addition, as implications for management practice, some strategies for better knowledge management in the organization are suggested for each type of innovation.

The main theoretical contribution focuses on the development of a conceptual model that structures the analyzed variables of the constructs “innovation process” and “innovation sectoral patterns”, allowing not only the characterization but also the comparative analysis of the representative organizations present in the sample.

One way to increase the availability and to add more value to exotic Brazilian fruits is to develop new products. However, prior to product development, there is a need to know consumer’s preferences and target audience. The purpose of this paper is to investigate the influence of different characteristics of Cerrado fruit preserves on the intention to purchase using conjoint analysis.

Conjoint analysis evaluated three factors with three levels each, defined by focus group technique. The attributes and levels evaluated were: flavor (marolo, marolo and soursoup, marolo, soursoup and sweet passion fruit), nutritional information (light, diet and absent) and health claims (aids reduction of cardiovascular disease risk; aids reduction of blood cholesterol; aids activation and regulation of the gastrointestinal system).

The results of conjoint analysis led to three consumers’ groups. Group 1 (majority) were more influenced by flavor (IR=26.5 percent) and nutritional information (IR=59.3 percent). Groups 2 and 3 were greatly influenced by flavor and nutritional information, respectively. Health claims influenced weakly on the intention to purchase regardless the groups. Thus, the concept of Cerrado fruit preserves for each group was different.

This research contributes to future studies, supporting the development of products based on Cerrado fruits and the variety of products on the market. There are few research works using conjoint analysis to evaluate consumer preferences in the early stages of new product development, which makes this paper even more relevant.

We present a critical literature review debating Brazilian research on social and environmental accounting (SEA). The aim of this study is to understand the role of politics in the construction of hegemonies in SEA research in Brazil. In particular, we examine the role of hegemony in relation to the co-option of SEA literature and sustainability in the Brazilian context by the logic of development for economic growth in emerging economies. The methodological approach adopts a post-structural perspective that reflects Laclau and Mouffe’s discourse theory. The study employs a hermeneutical, rhetorical approach to understand and classify 352 Brazilian research articles on SEA. We employ Brown and Fraser’s (2006) categorizations of SEA literature to help in our analysis: the business case, the stakeholder–accountability approach, and the critical case. We argue that the business case is prominent in Brazilian studies. Second-stage analysis suggests that the major themes under discussion include measurement, consulting, and descriptive approach. We argue that these themes illustrate the degree of influence of the hegemonic politics relevant to emerging economics, as these themes predominantly concern economic growth and a capitalist context. This paper discusses trends and practices in the Brazilian literature on SEA and argues that the focus means that SEA avoids critical debates of the role of capitalist logics in an emerging economy concerning sustainability. We urge the Brazilian academy to understand the implications of its reifying agenda and engage, counter-hegemonically, in a social and political agenda beyond the hegemonic support of a particular set of capitalist interests.

The objective of this paper is to draw up management guidelines on environmental sustainability for architectural and engineering design firms.

The paper is derived from a research experience between 2010 and 2018. That experience comes from three source sets: Management Development Program for Design Firms from the Research Line of Management Design, Department of Civil Construction Engineering, University of São Paulo in Brazil; papers including a doctoral thesis; and literature review. Revisiting and investigating processes were conducted by research questions, resulting in lessons learned, management difficulties and guidelines.

The guidelines were drawn up from a strategic sphere, understanding internal and external factors to the firm, diagnosis of the firm's management and sustainability, a building sustainability plan, implications of the plan for management processes, plan monitoring and control and plan evaluation.

The studies were mostly conducted in Brazil, and one of them in the USA. Other studies could be carried out in other countries comparing findings or implementing the guidelines.

The findings will provide feedback to Management Development Program for Design Firms (PDGEP) in the action research method. Moreover, the knowledge about firm's capabilities can advance understanding of architectural and engineering (AE) design firm management as support for sustainability, performance and building information modeling (BIM).

Architectural and engineering design firms are hardly discussed; design is treated in the building project context, giving prominence to technical solutions, not to management ones.