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- Discurso Web, Modelos TeĂłricos e Sistemas de Argumentação: ImplicaçÔes para a Tomada de DecisĂŁoPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloA crescente importĂąncia atribuĂda pelas organizaçÔes Ă tomada de decisĂŁo em contexto web requer que sejam definidos e implementados mecanismos mais eficientes para apoiar as atividades da mesma. As redes sociais, enquanto espaços de colaboração, permitem que os atores sociais interajam entre si independentemente do local e espaço onde se encontram. Um aspeto importante dos ambientes virtuais Ă© que, de uma forma ou de outra, se verifica a existĂȘncia de discussĂŁo argumentativa e nesse sentido a web constitui-se como uma excelente ferramenta para apoiar a representação, divulgação e recuperação do conhecimento, pois pode realçar a expressĂŁo argumentativa, devido Ă sua omnipresença e abertura. AtravĂ©s da captura e anĂĄlise do discurso web, Ă© possĂvel obter informação relevante que reflete a opiniĂŁo e a manifestação de pontos de vista que podem ser Ășteis para a tomada de decisĂŁo. Para o efeito, Ă© importante identificar e perceber a estrutura da rede de atores sociais, a comunicação, contexto, linguagem, linguĂstica e conteĂșdo do discurso web, visto que as palavras e frases estĂŁo sempre carregadas de sentidos e intençÔes, que podem ser definidas de forma diferente.A argumentação tem o seu foco nos diĂĄlogos com o objetivo de aumentar ou diminuir a aceitação de um ponto de vista, a fim de chegar a uma conclusĂŁo atravĂ©s de um raciocĂnio lĂłgico. Nesse contexto, temos assistido a um aumento importante no desenvolvimento de sistemas de colaboração centrados na web, que funcionam como facilitadores da argumentação. Nestes, diferentes pontos de vista podem ser apresentados, contestados e avaliados, e a tomada de decisĂŁo colaborativa Ă© efetuada atravĂ©s de debates e negociaçÔes entre um grupo de indivĂduos. Tendo em conta este novo paradigma, este trabalho objetivou consolidar conhecimentos associados ao discurso web, Ă argumentação e decisĂŁo, aos modelos teĂłricos de argumentação e aos sistemas de argumentação computacional para a web.
- From motivation and self-structure to a decision support framework for online social networksPublication . Antunes, Francisco; Freire, Manuela; Costa, JoĂŁo PauloData collected from online social networks offers new possibilities for supporting organizationsâ daily activities. It is also common knowledge that the opinion exchange in online social networks provides a decisive contribution in decision making. It is, thus, necessary to review and bare present the motivations by which people engage in online social network and the ways in which firms can make use of such motivations in order to take advantage of online social networks as information sources for decisionmaking support. To do so, the authors of this chapter developed the decision-support social networks to extract such information, which encompasses the intertwined use of human interaction and network structure by combining human capabilities, social network analysis (SNA), and automatic data mining. In this chapter, a brief summary of the performed case studies over the proposed information model is also presented.
- Applying Social Network Analysis and Data Mining Techniques to Support Decision-Making: A Case StudyPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloThe 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 OSNâs, 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 analysisPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloThis paper explores the use of social network analysis (SNA) on airlinesâ 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 airlineâs 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 airlineâs 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.
- From Motivation and Self-Structure to a Decision-Support Framework for Online Social NetworksPublication . Antunes, Francisco; Freire, Manuela; Costa, JoĂŁo PauloData collected from online social networks offers new possibilities for supporting organizationsâ daily activities. It is also common knowledge that the opinion exchange in online social networks provides a decisive contribution in decision making. It is, thus, necessary to review and bare present the motivations by which people engage in online social network and the ways in which firms can make use of such motivations in order to take advantage of online social networks as information sources for decisionmaking support. To do so, the authors of this chapter developed the decision-support social networks to extract such information, which encompasses the intertwined use of human interaction and network structure by combining human capabilities, social network analysis (SNA), and automatic data mining. In this chapter, a brief summary of the performed case studies over the proposed information model is also presented.
- Getting decision support from context-specific online social networks: a case studyPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloThe 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 OSNâs 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 OSNâs 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 customersâ requests, solely based on their Facebook posts, showing that the unstructured data of the webâs discourse can be used to support this kind of decision processes.
- Semantic Web Tools and Decision-MakingPublication . Antunes, Francisco; Freire, Manuela; Costa, JoĂŁo PauloSemantic Web technologies are intertwined with decision-making processes. In this paper the general objectives of the semantic web tools are reviewed and characterized, as well as the categories of decision support tools, in order to establish an intersection of utility and use. We also elaborate on actual and foreseen possibilities for a deeper integration, considering the actual implementation, opportunities and constraints in the decision-making context.
- Social Web Analysis for Decision Support: A Case StudyPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloIn 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.
- Exploring social network analysis techniques on decision supportPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloManagers are increasingly concerned in making timely and correct decisions, using adaptable decision structures, processes and mechanisms. For this purpose, they resort to web discourse capture and analysis to obtain opinions that express different points of view, regarding organizational decision-making. Since communication and interaction among groups are very important in group decision, the exchanged and shared contents, as well as a social network analysis (SNA), can play an important role in this process. Understanding the interactions within a social network and how they can support decision-making is an important issue, representing the main motivation for this work. For the study presented in this paper, to understand how organizations can strategically use online communication as a decision support tool, we chose to use Facebook, where social actors gather around the same focus of interest or affinity (friends, co-workers, etc.) and, additionally, it is possible to create discussion groups for defining a problem, limit group members and context argument. In addition, we chose an ego-centric analysis focused on a single actor, instead of the network as a whole, to get a good picture of the âlocalâ or his âneighborsâ networks. The analyzed data were collected from Facebook and afterwards we applied SNA techniques in order to draw some conclusions.
- A Semantics Extraction Framework for Decision Support in Context-Specific Social Web NetworksPublication . Freire, Manuela; Antunes, Francisco; Costa, JoĂŁo PauloWe are now part of a networked society, characterized by the intensive use and dependence of information systems that deals with communication and information, to support decision-making. It is thus clear that organizations, in order to interact effectively with their customers, need to manage their communication activities at the level of online channels. Monitoring these communications can contribute to obtain decision support insights, reduce costs, optimize processes, etc. In this work, we semantically studied the discursive exchanges of a Facebook group created by a strawberriesâ seller, in order to predict, through Social Network Analysis (SNA) and semantic analysis of the posts, the quantities to be ordered by customers. The obtained results show that the unstructured data of the Webâs speech can be used to support the decision through SNA.