Applying Text Mining on Electronic Messages for Competitive Intelligence

Oliveira, José Palazzo M. de; Loh, Stanley; Wives, Leandro Krug; Scarinci, Rui Gureghian; Musa, Daniela Leal; Silva, Lydia; Zambenedetti, Christian

doi:10.1007/978-3-540-30077-9_28

Cited by 8 publications

(7 citation statements)

References 11 publications

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“…Applying text and web mining to these data adds a richness and depth to the patterns already uncovered through the company's data mining efforts. Text mining applies the same analytical functions of data mining to the domain of textual information, relying on sophisticated, text analysis techniques that distill information from free-text documents (Dorre et al, 1999;Oliveira et al, 2004). Web mining is a form of data mining used to discover patterns from the web.…”

Section: Introductionmentioning

confidence: 99%

Advanced analytics: opportunities and challenges

Bose

2009

Industrial Management &Amp; Data Systems

243

150

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Purpose -Advanced analytics-driven data analyses allow enterprises to have a complete or "360 degrees" view of their operations and customers. The insight that they gain from such analyses is then used to direct, optimize, and automate their decision making to successfully achieve their organizational goals. Data, text, and web mining technologies are some of the key contributors to making advanced analytics possible. This paper aims to investigate these three mining technologies in terms of how they are used and the issues that are related to their effective implementation and management within the broader context of predictive or advanced analytics. Design/methodology/approach -A range of recently published research literature on business intelligence (BI); predictive analytics; and data, text and web mining is reviewed to explore their current state, issues and challenges learned from their practice. Findings -The findings are reported in two parts. The first part discusses a framework for BI using the data, text, and web mining technologies for advanced analytics; and the second part identifies and discusses the opportunities and challenges the business managers dealing with these technologies face for gaining competitive advantages for their businesses. Originality/value -The study findings are intended to assist business managers to effectively understand the issues and emerging technologies behind advanced analytics implementation.

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Section: Introductionmentioning

confidence: 99%

Advanced analytics: opportunities and challenges

Bose

2009

Industrial Management &Amp; Data Systems

243

150

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“…Santos and Correia (2010) define effective CI as a continuous process involving the legal and ethical collection of information and analysis that does not avoid unwelcome conclusions as well as the controlled dissemination of actionable intelligence to decision makers. While Oliveira et al (2004) define CI as a business activity whose goal is to provide strategic information about markets for management activities, they continue by stating organizations can use CI to analyze how saturated a market is, or the kind of players present and if there is space for a niche offer.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…In the CI arena, concept analysis allows for player identification within a market, products and services, their characteristics, benefits and events of the real world, vendors’ strategies and opinions of people and media companies (de Oliveira et al , 2004). Such segmentation helps compare strategies and look for common themes or differences, such as saturated markets, market niches, most popular products and new services (de Oliveira et al , 2004).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Organizational experience of social media: impacts on competitive intelligence

Carvalho¹,

Picoto

Busch³

2021

VJIKMS

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Purpose The paper aims to clarify the potential impact of data gathered from social media (SM) in the competitive intelligence (CI) process of organizations. As use of SM expands, analysis of this data becomes a critical business need providing essential support for decision makers. This paper seeks to examine how SM be used to enhance CI in an organizational context. Design/methodology/approach This paper adopted an exploratory mixed-method approach followed by a sequential and equal status design, with qualitative semi-structured interviews, accounting for the qualitative study and serving as precursor to a quantitative structured survey. Interviewees included a university professor and CI consultant, an SM analyst and a subject in a management position – all in the field of CI. A survey was sent to Fortune 1000 companies. Some 227 companies replied. Findings The findings were that the majority of respondents produce CI reports at least monthly, and that information transmitted mainly by presentation within organizations. Over 70% of companies outsource CI activities to specialized firms, while 80.9% of organizations felt CI improved their relationship with their customers. Not surprisingly, as the number of people dedicated to CI activities increased, the likelihood of an organization hiring outside companies specializing in CI diminished. Research limitations/implications All organizations sampled were large US companies; thus, small- and medium-sized enterprises were excluded, as were non-US viewpoints. As survey respondents were anonymous, the source of data at the level of the individual is missing. Finally, only three interviewees provided the qualitative data. Practical implications This investigation determined organizations should have an established and well-structured CI department. Furthermore, such a department should have between five and ten employees to maximize the potential. Outsourcing depends on the company’s specific needs. Nevertheless, regardless of whether it outsources CI activities or not, each firm should monitor SM to enhance the CI process. Originality/value Much SM-based CI is either non-existent or in “embryotic” stages in most companies, and therefore still a work in progress. Furthermore, as SM is a relatively new phenomenon, studies supporting its implementation are scarce. Companies stand to gain significant improvements to CI if SM is effectively used.

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“…Diferentemente da Mineração de Dados, a Mineração de Textos suporta conjuntos de dados não-estruturados e semiestruturados, como correios eletrônicos, arquivos HTML e documentos de texto em geral (VIJAYARANI; MUTHULAKSHMI, 2013). Oliveira et al (2004) indicam usos da Mineração de Textos em estudos econômicos, descobrindo associações entre países e organizações ou realizando previsões sobre tecnologias, e na Internet, revelando associações, autoridades e eixos (hubs) de alguma área, por exemplo.…”

Section: Mineração De Textosunclassified

Análise de dados em artigos recuperados da Web of Science (WoS)

Carvalho

Tsunoda

2018

Encontros Bibli

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Dado o contexto da Mineração de Dados e da Mineração de Textos, objetiva-se analisar dados recuperados da Web of Science (WoS). Pretende-se identificar padrões nos estudos sobre Mineração de Textos voltados a escolha de ferramentas a serem utilizadas na aplicação de método de mineração de dados. Recuperaram-se referências de artigos no formato BibTeX na plataforma WoS. Desenvolveu-se uma aplicação para inserção de dados do formato BibTeX para um banco de dados MySQL. Com base nas características encontradas, elegeram-se a ferramenta R e algoritmo Apriori para utilização em parte dos dados. Extraíram-se dados de ferramentas, métodos, palavras-chave, termos, periódicos, países e autores presentes nos registros. A aplicação do Apriori resultou em treze regras de associação. A exploração dos dados de artigos provenientes da WoS revelou características dos estudos da área de Mineração de Textos. Trabalhos futuros podem adaptar a aplicação usada neste estudo e aplicar outros métodos de mineração no conjunto de dados.

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Applying Text Mining on Electronic Messages for Competitive Intelligence

Cited by 8 publications

References 11 publications

Advanced analytics: opportunities and challenges

Advanced analytics: opportunities and challenges

Organizational experience of social media: impacts on competitive intelligence

Análise de dados em artigos recuperados da Web of Science (WoS)

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