Centre for Business and Economics Research - University of Coimbra

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Publications

Getting decision support from context-specific online social networks: a case study

Publication . Freire, Manuela; Antunes, Francisco; Costa, João Paulo

The combination between online social networks (OSN) and decision processes provides a favorable social data analysis paradigm for efficient decision support and business-processes integration. This paper presents a framework for handling OSN’s contents, providing a simpler and effective approach for information retrieval and processing. The objective is to address a decision-making problem, by using that framework to extract, process, structure and analyze the OSN’s data. The decision process is not only guided by OSN data, but also by social network analysis methodology and is entirely based on the communications among social media users. Our framework combines two different, though complementary, perspectives: the analysis of the interactions among users and the semantic analysis of their discourses. In addition, it aims to bridge technology and manual-based approaches, thus enhancing the possibilities for making a better use of an OSN, using free-available software. The case study, herein, aims to estimate customers’ requests, solely based on their Facebook posts, showing that the unstructured data of the web’s discourse can be used to support this kind of decision processes.

2022-03-04Journal article

Open access

Social Web Analysis for Decision Support: A Case Study

Publication . Freire, Manuela; Antunes, Francisco; Costa, João Paulo

In this study, we focused on analyzing customer-generated data on Facebook to explore how textual content on a social web can provide valuable information for decision support. To accomplish this goal, we used several techniques that included social network analysis (SNA), natural language processing (NLP), data mining (DM), and machine learning (ML), integrating them with artificial intelligence approaches. Our analysis aimed to harness the information generated during the Volkswagen pollutant emissions situation in a case study that was conducted using the textual content from 10,642 posts, that represented the interactions of 25,877 users over a span of twenty-two weeks. The results demonstrated that monitoring online social networks (OSNs) can significantly enhance decision-making processes and might help to mitigate potential damages to brands/businesses. By leveraging the proposed methodological approach, a set of orientations for decision-making was extracted, providing valuable guidance for brand management and reputation protection. Overall, this study highlights the importance of analyzing textual content on OSNs and leveraging advanced computational techniques to improve decision support.

2023Book part

Open access

Applying Social Network Analysis and Data Mining Techniques to Support Decision-Making: A Case Study

Publication . Freire, Manuela; Antunes, Francisco; Costa, João Paulo

The key goal of this work is to explore interactions and discursive exchanges between social users, to extract information towards decision support. We analyzed customer-generated data on Facebook, during a period of a ten-day strike, of a well-known airline company. The main goal was to check service and responsiveness of the airline, and also to develop indicators that might enable reviewing and reinforce strategies to be used in customer service response to strike events. The authors aim to investigate the possibility of structuring data, collected from OSN’s, incorporating human interaction and network structure, using SNA to study the network from a duo fold manner: the web discourse, which depends on the transmission of information; and the interaction among social users, as information disseminators. Our work intends to determine whether social users and their interactions are consistent with the creation of indicators for decision support.

2022Book part

Open access

Assessing Psychosocial Work Conditions: Preliminary Validation of the Portuguese Short Version of the Copenhagen Psychosocial Questionnaire III

Publication . Pinto, Ana; Carvalho, Carla; Mónico, Lisete S.; Moio, Isabel; Alves, Joel; Lima, Tânia M.

The working environment is a crucial aspect to considerfor guaranteeing a sustainable life. However, workers are exposed to various health risks daily, namely, psychological risks. These risks can be due to imbalances on the part of the workers themselves or to organisational and interfunctional risk factors arising from interactions within companies and the challenges of professional responsibilities. Over the past 20 years, the Copenhagen Psychosocial Questionnaire (COPSOQ) has become one of the most prominent tools for assessing psychological and social factors at work. This study aimed to present, discuss, and evaluate aspects of the cultural adaptation and preliminary psychometric validation of the short version of COPSOQ III for a Portuguese sample. For this purpose, we used data from 361 participants employed in the industrial (30.7%) and services (69.3%) sectors across various regions of Portugal. A third-order confirmatory factor analysis (CFA) was performed using AMOS, revealing an acceptable fit. The results also demonstrate the robustness of the measurement model, confirming its reliability and validity. In light of some limitations of this preliminary study, directions for future research are proposed. Thus, a tool for assessing psychosocial risks is disseminated, making it possible to achieve more sustainable working environments where the operator’s health and well-being are prioritised.

2024-08-29Journal article

Open access

Enhancing decision-making support by mining social media data with social network analysis

Publication . Freire, Manuela; Antunes, Francisco; Costa, João Paulo

This paper explores the use of social network analysis (SNA) on airlines’ online social networks (OSNs) to extract valuable information for decision support, by analyzing interactions and discursive exchanges between users. The research is focused on fostering customer service of an airline company during a strike period, namely by detecting influential customers (whether satisfied or dissatisfied), address pending requests, and enhancing customer satisfaction, thus promoting issue-solving, and increasing responsiveness. The methodology involves analyzing data from the Facebook account of an airline company, using SNA to structure the data, and calculating metrics to detect possible situations to be addressed by customer service. The research concludes that it is possible to extract valuable information for decision support by analyzing the metrics that were built over the interactions and discursive exchanges between OSN users. SNA metrics enable to measure airline’s call-center performance in terms of speed of answer and customer satisfaction, to identify active users requiring additional support, as well as highly influential customers who may impact on the overall customer satisfaction, thus helping to resolve issues more efficiently. This study provides both theoretical and practical implications: it contributes to the existing literature by integrating social interaction and SNA for decision support in airline’s service context; and it provides practical insights into how companies can use SNA metrics to improve customer service. The research also highlights and corroborates the importance of monitoring social media interactions for decision-making and improving customer service.

2023-05-15Journal article

Open access