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Journal ArticleDOI

Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions

TL;DR: This paper presents a novel model for experts to carry out Group Decision Making processes using free text and alternatives pairwise comparisons and introduces two ways of applying consensus measures over the Group decision Making process.
Abstract: Social networks are the most preferred mean for the people to communicate. Therefore, it is quite usual that experts use them to carry out Group Decision Making processes. One disadvantage that recent Group Decision Making methods have is that they do not allow the experts to use free text to express themselves. On the contrary, they force them to follow a specific user–computer communication structure. This is against social network nature where experts are free to express themselves using their preferred text structure. This paper presents a novel model for experts to carry out Group Decision Making processes using free text and alternatives pairwise comparisons. The main advantage of this method is that it is designed to work using social networks. Sentiment analysis procedures are used to analyze free texts and extract the preferences that the experts provide about the alternatives. Also, our method introduces two ways of applying consensus measures over the Group Decision Making process. They can be used to determine if the experts agree among them or if there are different postures. This way, it is possible to promote the debate in those cases where consensus is low.
Citations
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Journal ArticleDOI
TL;DR: This work proposes the definition of four different dimensions, namely Pattern & Knowledge discovery, Information Fusion & Integration, Scalability, and Visualization, which are used to define a set of new metrics (termed degrees) in order to evaluate the different software tools and frameworks of SNA.

134 citations

Journal ArticleDOI
TL;DR: The challenges of large-scale group decision making are summarized and a state-of-the-art survey of main achievements in this field is presented to provide existing research gaps and future directions that require further consideration.
Abstract: The arrival of Big Data era has brought large, complex, and growing data generated from numerous sources. Due to the power in felicitous decision making based on diverse and large data, Big Data can be used in distinct disciplines, especially in social Big Data such as e-commerce, e-marketplaces and social media platforms. As a result, the large-scale group decision making, in which a large number of decision-makers take part in the decision-making process, has become a much-talked-about topic in decision science. Because of the characteristics of social Big Data, much more information in large-scale group decision making will arise than conventional group decision making. Information is a key factor that influences the performance of decision-makers. Therefore, how to manage the challenges from conventional group decision making to large-scale group decision making is a critical and interesting research topic. Up to now, many studies have been published to tackle these challenges. The objective of this study is to summarize the challenges and present a state-of-the-art survey of main achievements in this field. We also provide existing research gaps and future directions that require further consideration. It is hoped that our study could give insights for scholars and practitioners along the developments and promising research of large-scale group decision making.

126 citations

Posted Content
01 Mar 2018
TL;DR: In this article, a multi-criteria group decision-making method using fuzzy ontologies reasoning procedures is presented. But the authors only require experts to provide the importance of a small set of criteria values, making it possible for experts to perform multicriteria groups decision making procedures without having to directly deal with them.
Abstract: Classic multi-criteria group decision making models that have a high amount of alternatives are unmanageable for the experts. This is because they have to provide one value per each alternative and criteria. In this paper, we focus on solving this issue by carrying out multi-criteria group decision making methods using a different novel approach. Concretely, fuzzy ontologies reasoning procedures are used in order to automatically obtain the alternatives ranking classification. Thanks to our novel methodology, experts only need to provide the importance of a small set of criteria values making it possible for experts to perform multi-criteria group decision making procedures that have a high amount of alternatives without having to directly deal with them. Furthermore, in order to allow experts to provide their preferences in a comfortable way, multi-granular fuzzy linguistic modelling is used in order to allow each expert to choose the linguistic label set that better fits him/her.

106 citations

Journal ArticleDOI
TL;DR: A framework of personalized feedback mechanism to help multiple inconsistent experts to reach consensus in group decision making by allowing to select different feedback parameters according to individual consensus degree is proposed.
Abstract: This article proposes a framework of personalized feedback mechanism to help multiple inconsistent experts to reach consensus in group decision making by allowing to select different feedback parameters according to individual consensus degree. The general harmony degree (GHD) is defined to determine the before/after feedback difference between the original and revised opinions. It is proved that the GHD index is monotonically decreasing with respect to the feedback parameter, which means that higher parameter values will result in higher changes of opinions. An optimization model is built with the GHD as the objective function and the consensus thresholds as constraints, with the solution being personalized feedback advices to the inconsistent experts that keep a balance between consensus (group aim) and independence (individual aim). This approach is, therefore, more reasonable than the unpersonalized feedback mechanisms in which the inconsistent experts are forced to adopt feedback generated with only consensus target without considering the extent of the changes acceptable by individual experts. Furthermore, the following interesting theoretical results are also proved: 1) the personalized feedback mechanism guarantees that the increase of consensus level after feedback advices are implemented; 2) the GHD by the personalized feedback mechanism is higher than that of the unpersonalized one; and 3) the personalized feedback mechanism generalizes the unpersonalized one as it is proved the latter is a particular type of the former. Finally, a numerical example is provided to model the feedback process and to corroborates these results when comparing both feedback mechanism approaches.

70 citations


Cites background from "Carrying out consensual Group Decis..."

  • ...The CRP consists of four steps: (1) Opinions representation; (2) Consensus Measure; (3) Inconsistency identification; and (4) Feedback Mechanism [4], [18], [57]....

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References
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Journal ArticleDOI
TL;DR: Much of what constitutes the core of scientific knowledge may be regarded as a reservoir of concepts and techniques which can be drawn upon to construct mathematical models of various types of systems and thereby yield quantitative information concerning their behavior.

12,530 citations

Proceedings ArticleDOI
22 Aug 2004
TL;DR: This research aims to mine and to summarize all the customer reviews of a product, and proposes several novel techniques to perform these tasks.
Abstract: Merchants selling products on the Web often ask their customers to review the products that they have purchased and the associated services. As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds or even thousands. This makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product. It also makes it difficult for the manufacturer of the product to keep track and to manage customer opinions. For the manufacturer, there are additional difficulties because many merchant sites may sell the same product and the manufacturer normally produces many kinds of products. In this research, we aim to mine and to summarize all the customer reviews of a product. This summarization task is different from traditional text summarization because we only mine the features of the product on which the customers have expressed their opinions and whether the opinions are positive or negative. We do not summarize the reviews by selecting a subset or rewrite some of the original sentences from the reviews to capture the main points as in the classic text summarization. Our task is performed in three steps: (1) mining product features that have been commented on by customers; (2) identifying opinion sentences in each review and deciding whether each opinion sentence is positive or negative; (3) summarizing the results. This paper proposes several novel techniques to perform these tasks. Our experimental results using reviews of a number of products sold online demonstrate the effectiveness of the techniques.

7,330 citations

Book
30 Dec 1991
TL;DR: In this article, the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work, is described and discussed. But it is argued that the analysis of social networks is not a purely static process.
Abstract: This paper reports on the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work. It is argued...

6,366 citations

MonographDOI
01 Jan 2012
TL;DR: Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals.
Abstract: This book introduces the non-specialist reader to the principal ideas, nature and purpose of social network analysis. Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals. Social network theory maps these relationships between individual actors. Though relatively new on the scene it has become hugely influential across the social sciences. Assuming no prior knowledge of quantitative sociology, this book presents the key ideas in context through examples and illustrations. Using a structured approach to understanding work in this area, John Scott signposts further reading and online sources so readers can develop their knowledge and skills to become practitioners of this research method. A series of Frequently Asked Questions takes the reader through the main objections raised against social network analysis and answers the various queries that will come up once the reader has worked their way through the book.

5,439 citations

Journal ArticleDOI
TL;DR: The point of this note is that fuzzy logic plays a pivotal role in CW and vice-versa and, as an approximation, fuzzy logic may be equated to CW.
Abstract: As its name suggests, computing with words (CW) is a methodology in which words are used in place of numbers for computing and reasoning. The point of this note is that fuzzy logic plays a pivotal role in CW and vice-versa. Thus, as an approximation, fuzzy logic may be equated to CW. There are two major imperatives for computing with words. First, computing with words is a necessity when the available information is too imprecise to justify the use of numbers, and second, when there is a tolerance for imprecision which can be exploited to achieve tractability, robustness, low solution cost, and better rapport with reality. Exploitation of the tolerance for imprecision is an issue of central importance in CW. In CW, a word is viewed as a label of a granule; that is, a fuzzy set of points drawn together by similarity, with the fuzzy set playing the role of a fuzzy constraint on a variable. The premises are assumed to be expressed as propositions in a natural language. In coming years, computing with words is likely to evolve into a basic methodology in its own right with wide-ranging ramifications on both basic and applied levels.

3,093 citations