Topic Modeling and Transfer Learning for Automated Surveillance of Injury Reports in Consumer Product Reviews

Many modern firms and interest groups are tasked with the challenge of monitoring the status and performance of a bevy of distinct products. As online user-generated content has increased in volume, new unstructured data sources are available for mining unique insights. Reports of injuries arising as a result of product usage are particularly concerning. In this paper, we utilize complimentary approaches to address this problem. We analyze two novel datasets; first, a government-maintained dataset of hazard and injury reports and second, a large dataset of cross-industry consumer product reviews manually coded for the presence of hazard and injury reports. We apply an unsupervised topic modeling approach to characterize the hazard and injury reports detected. Then, we implement a supervised transfer learning technique, using information obtained from the government-maintained dataset to detect hazard and injury reports in online reviews. Our results offer improved surveillance for monitoring hazards across multiple industries

Marketing intelligence from data mining perspective : A literature review

The digital transformation enables enterprises to mine big data for marketing intelligence on markets, customers, products, and competitor. However, there is a lack of a comprehensive literature review on this issue. With an aim to support enterprises to accelerate the digital transformation and gain competitive advantages through exploiting marketing intelligence from big data, this paper examines the literature in the period from 2001–2018. Consequently, 76 most relevant articles are analyzed based on four marketing intelligence components (Markets, Customers, Products, and Competitors) and six data mining models (Association, Classification, Clustering, Regression, Prediction, and Sequence Discovery). The findings of this study indicate that the research area of product and customer intelligence receives most research attention. This paper also provides a roadmap to guide future research on bridging marketing and information systems through the application of data mining to exploit marketing intelligence from big data

Emergence of Things Felt: Harnessing the Semantic Space of Facebook Feeling Tags

In 2013 Facebook launched a feature allowing users to add a feeling tag to their posts. We have collected 18 months worth of such public posts. Our aim is to map the semantic space of ‘Facebook feelings’ to understand patterns in how feelings are tagged and how they can be described in terms of valence and arousal. Our findings reveal temporal and social patterns in the most commonly shared feelings. In line with the ‘exhibitional’ nature of Facebook, our analyses indicate that ‘extreme’ feelings, such as excitement and anger, may be expressed in even more extreme levels of both valence and arousal. Facebook also provides novel emotional scripts (e.g., “meh”) that help people express feelings in ways that traditionally socialized feelings do not. This understanding of the semantic space of ‘Facebook feelings’ ultimately serves to inform the development of an automatic ‘Feelings Meter’

Effectiveness of Corporate Social Media Activities to Increase Relational Outcomes

This study applies social media analytics to investigate the impact of different corporate social media activities on user word of mouth and attitudinal loyalty. We conduct a multilevel analysis of approximately 5 million tweets regarding the main Twitter accounts of 28 large global companies. We empirically identify different social media activities in terms of social media management strategies (using social media management tools or the web-frontend client), account types (broadcasting or receiving information), and communicative approaches (conversational or disseminative). We find positive effects of social media management tools, broadcasting accounts, and conversational communication on public perception

A Novel Design Science Approach for Integrating Chinese User-Generated Content in Non-Chinese Market Intelligence

Market research has long relied on reactive means of data gathering, such as questionnaires or focus groups. With the wide-spread use of social media, millions of comments about customer opinions and feedback regarding products and brands are available. However, before using this ‘wisdom of the crowd’ as a source for marketing research, several challenges have to be tackled: the sheer volume of posts, their unstructured format, and the dozens of different languages used on the internet. All of them make automated usage of this data challenging. In this paper, we draw on dashboard design principles and follow a design science research approach to develop a framework for search, integration, and analysis of cross-language user-generated content. With ‘MarketMiner’, we implement the framework in the automotive industry by analyzing Chinese auto forums. The results are promising in that MarketMiner can dramatically improve utilization of foreign-language social media content for market intelligence purposes

Content mining framework in social media: A FIFA world cup 2014 case analysis

© 2016 Elsevier B.V.This paper proposes a social media content mining framework that consists of seven phases. The framework was tested empirically during the FIFA World Cup 2014 at Curitiba (Brazil) as one of the main host city destinations. The research focused on the mining of Twitter content with tourist services ontology (hospitality, food and beverages, and transportation). In total, 58,686 valid messages were collected, analyzed, and associated with an application ontology. Content analysis demonstrated an accurate real-time reflection of tourism services. The framework is effective to collect relevant content and identify popular topics in social media toward strategic and operational tourism management

Análise das ações de promoção de Miami (FL/EUA) como destino turístico pelo Greater Miami Convention and Visitors Bureau

Orientadora : Profª Drª Márcia S.M. NakataniDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Humanas, Programa de Pós-Graduação em Turismo. Defesa: Curitiba, 31/08/2016Inclui referências : f. 89-92Resumo: Esta dissertação tem como objetivo analisar como a informação turística, gerada pelas pesquisas de mercado, influencia as ações de promoção de Miami (Flórida/EUA) como destino turístico. Considerando a comunicação dentro das pesquisas sobre marketing turístico pretende-se com este estudo de caso ampliar as pesquisas sobre como as Destination Marketing Organizations utilizam a informação turística na promoção de localidades como destinos turísticos. Como procedimentos metodológicos foram conduzidos estudos bibliográficos e documentais, por meio de fichamentos e resumos, realizadas entrevistas semi-estruturadas e visitas à localidade escolhida como estudo de caso. Os dados coletados estão relacionados à entender as ações de marketing realizadas, a estrutura de organização da DMO oficial de Miami, e a atuação do Greater Miami Conventionand Visitor Bureau - GMCVB e suas estratégias de marketing e descrição de seus principais parceiros (stakeholders). Foram identificadas suas principais ações de promoção, assim como principais funções dos stakeholders - parceiros do GMCVB. Conclui-se desta forma que o GMCVB atua localmente e em países emissores com campanhas inovadoras de marketing baseadas na segmentação do turismo e pesquisas de mercado realizadas sobre seus visitantes. Palavras-chave: Informação turística. Destination Marketing Organization. Promoção de Destinos Turísticos. Greater Miami Convention & Visitors Bureau.Abstract: This thesis aims to analyze how the tourist information generated by market research influences Miami promotion actions (Florida / USA) as a tourist destination. Considering the communication within the research on tourism marketing (Ruschmann, 1999; MIDDLETON; CLARKE, 2002; Nielsen, 2002; BALANZA; NADAL, 2003; REY., 2004; Kotler et al, 2009; Morrison, 2012), is intended to this case of study expand research on the Destination Marketing Organizations use the tourist information in promoting locations. As methodological procedures were conducted bibliographic and documentary studies, abstracts, semi-structured interviews and visits to the location chosen as a case study. The primary data collection refers to the marketing actions taken, the organizational structure of the official DMO of Miami, Greater Miami Conventionand Visitor Bureau - GMCVB, their marketing strategies and description of its main partners (stakeholders). It follows therefore that the GMCVB acts locally and in source countries with innovative marketing campaigns based on tourism segmentation and market research on your visitors. its main promotion activities have been identified, as well as key roles of stakeholders partners of GMCVB. Keywords: Tourist information; BMD; Management Marketing destinations; Greater Miami Convention and Visitors Bureau; Promotion actions; Market research; competitive tourist destinations; Branding; Place Marketing

Conceptualizing the Electronic Word-of-Mouth Process: What We Know and Need to Know About eWOM Creation, Exposure, and Evaluation

Electronic word of mouth (eWOM) is a prevalent consumer practice that has undeniable effects on the company bottom line, yet it remains an over-labeled and under-theorized concept. Thus, marketers could benefit from a practical, science-based roadmap to maximize its business value. Building on the consumer motivation–opportunity–ability framework, this study conceptualizes three distinct stages in the eWOM process: eWOM creation, eWOM exposure, and eWOM evaluation. For each stage, we adopt a dual lens—from the perspective of the consumer (who sends and receives eWOM) and that of the marketer (who amplifies and manages eWOM for business results)—to synthesize key research insights and propose a research agenda based on a multidisciplinary systematic review of 1050 academic publications on eWOM published between 1996 and 2019. We conclude with a discussion of the future of eWOM research and practice