Estimating the importance of consumer purchasing criteria in digital ecosystems

Peláez, José Ignacio; Cabrera, Francisco E.; Vargas, Luis G.

doi:10.1016/j.knosys.2018.07.023

Cited by 15 publications

(8 citation statements)

References 18 publications

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“…The corpus of communications was analyzed using the natural language analysis tools (ANL) provided by the IBM Watson Analytics service [17]. Then, the corpus was analyzed again for confirmation purposes using the Interval Majority Aggregation Operator (ISMA-OWA) [18], which is designed for decision making in social media with consistent data, leveraged by the combination of computational intelligence and big data techniques [19].…”

Section: Study Population and Data Collectionmentioning

confidence: 99%

The Contagion of Sentiments during the COVID-19 Pandemic Crisis: The Case of Isolation in Spain

Iglesias-Sánchez

Vaccaro

Cabrera

et al. 2020

IJERPH

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This study examines how confinement measures established during the COVID-19 pandemic crisis affected the emotions of the population. For this purpose, public sentiment on social media and digital ecosystems in Spain is analyzed. We identified affective tones towards media and citizens published on social media focusing on six basic emotions: anger, fear, joy, sadness, disgust and uncertainty. The main contribution of this work is the evidence of contagious sentiments and, consequently, the possibility of using this new dimension of social media as a form of a “collective therapy”. This paper contributes to understanding the impact of confinement measures in a pandemic from the point of view of emotional health. This analysis provides a set of practical implications that can guide conceptual and empirical work in health crisis management with an alternative approach, especially useful for decision-making processes facing emergency responses and health crises, even in an unprecedented global health crisis such as the traumatic events caused by the COVID-19 disease.

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Section: Study Population and Data Collectionmentioning

confidence: 99%

The Contagion of Sentiments during the COVID-19 Pandemic Crisis: The Case of Isolation in Spain

Iglesias-Sánchez

Vaccaro

Cabrera

et al. 2020

IJERPH

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“…is a partial assessment of in relation to criterion . From it is possible to estimate an overall measure ( ) for each alternative using an aggregation operator : ℝ → ℝ (Peláez et al, 2018).…”

Section: The Profile Of the Alternative Described By The Criterion Mumentioning

confidence: 99%

“…Automated procedures can be used to obtain communications from open or private sources, such as Twitter or Facebook APIs. We obtained relevant communications related to rural tourism in Málaga province using the capture → extraction → semantic analysis approach, which has proven useful for similar tasks (Peláez et al, 2018). Firstly, communications were acquired from social networks using passive (API) or active (scraping) methods and stored in a data pool.…”

Section: Assessment Of Communications From Social Media Platformsmentioning

confidence: 99%

“…Furthermore, SNA is a powerful tool for tourism research that, at a relatively low cost, can be used to manage and process large datasets of comments, ratings, and shares from different online communities (Brown, 2015;Liu & Liang, 2016;Monterrubio, 2017;Otte & Rousseau, 2002;Schroeder, Pennington-Gray, Kim & Liu-Lastres, 2018;Zeng & Gerritsen, 2014). However, the heterogeneous nature of unsolicited opinions, the complexity of natural language assessment, and differences in the characteristics of the social-data sources hinder the accurate assessment of preferences (Peláez, Cabrera & Vargas, 2018;Rai et al, 2018;Sandberg, Jaradat & Dokoohaki, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Hybrid preference assessment for tourism research using solicited and unsolicited opinions: an application in rural tourism

Fernández-Gámez

Bendodo-Benasayag

Serrano³

et al. 2020

TMS

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Social media analysis is a powerful tool for tourism research that, at a relatively low cost, can be used to manage and process large datasets of comments, ratings, and shares from different online communities. However, the heterogeneous nature of unsolicited opinions, the complexity of natural language assessment, and differences in the characteristics of social-data sources hinder the accurate assessment of preferences. Likewise, the use of solicited data sources, such as direct polling, is typically resource-intensive, time-consuming, and geographically limited. We analyze a hybrid approach that combines active polling with passive social media analysis to rate tourist experience. To this end, we present a novel multiple criteria decision analysis model for preference-extraction from solicited and unsolicited data. The proposed approach can significantly reduce the number of polls required to accurately assess the preferences of a community, especially when surveying rural destinations, which are sparsely populated geographic areas situated outside cities and towns.

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“…Sci. 2020, 9, 23 2 of 20 (Peláez et al 2018;Sebastian 2014), collecting customer feedback from social media, websites or online forms (Liu and Ji 2018), as well as knowing what types of stimuli impact people (Baraybar-Fernández et al 2017), understanding the reasons that motivates people to like a product/service (Peláez et al 2019b), conducting market research (Wereda and Woźniak 2019), categorizing customer service requests and predicting consumer behavior, among others (Baron et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Opinion Mining and Sentiment Analysis in Marketing Communications: A Science Mapping Analysis in Web of Science (1998–2018)

2020

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Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.

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Estimating the importance of consumer purchasing criteria in digital ecosystems

Cited by 15 publications

References 18 publications

The Contagion of Sentiments during the COVID-19 Pandemic Crisis: The Case of Isolation in Spain

The Contagion of Sentiments during the COVID-19 Pandemic Crisis: The Case of Isolation in Spain

Hybrid preference assessment for tourism research using solicited and unsolicited opinions: an application in rural tourism

Opinion Mining and Sentiment Analysis in Marketing Communications: A Science Mapping Analysis in Web of Science (1998–2018)

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