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Research Project
Institute for Systems Engineering and Computers at Coimbra - INESC Coimbra
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Publications
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.
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.
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.
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.
Wearable solution for health monitoring of car drivers
Publication . Baiense, João Pedro; Coelho, Paulo Jorge; Pires, Ivan Miguel; Velez, Fernando J.
The need for creative solutions in real-time health monitoring has been highlighted by the rise in health-related incidents involving drivers of motor vehicles. It has led to the development of wearable technology that seamlessly integrates with the Internet of Medical Things (IoMT) to improve driver safety and healthcare responsiveness. The development of a revolutionary wearable technology system is presented in this study as an innovative approach to vehicle safety and healthcare. This system's real-time ability to track a driver's health is a significant development in guaranteeing driver safety and wellness. The study examines the hardware component's complex design and implementation, particularly concerning the printed circuit board (PCB) layout and electrical schematic. The gadget emphasizes wearability, robustness, affordability, and user-friendliness and is a shining example of valuable and effective medical technology. The research delves deeper into possible improvements for the system, like adding complex algorithms and a user-friendly interface. Enhancing user involvement and system intelligence hopes to maximize the system's potential for real-time health monitoring. The significance of this study in utilizing Internet of Medical Things (IoMT) technology is highlighted by its junction with multiple fields, including electronics, hardware engineering, human-computer interaction, and health informatics. This dissertation emphasizes the potential of wearable technology in bridging the gap between healthcare monitoring and vehicle safety by focusing on real-time health monitoring in the automotive context
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Funders
Funding agency
Fundação para a Ciência e a Tecnologia
Funding programme
6817 - DCRRNI ID
Funding Award Number
UIDB/00308/2020