Tracking Topic Evolution in News Environments

Viermetz, Maximilian; Skubacz, Michal; Ziegler, Cai-Nicolas; Seipel, Dietmar

doi:10.1109/cecandeee.2008.112

Cited by 11 publications

(3 citation statements)

References 9 publications

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“…A great deal of researchers develop methods for identifying and tracking trends on the web. For example, Viermetz et al (2008) monitor short‐term and long‐term topic trends. Bun and Ishizuka (2006) outline a system for discovering emerging topical issues and changes in topics.…”

Section: Related Workmentioning

confidence: 99%

Mining consumer dialog in online forums

Kaiser

Bodendorf²

2012

Internet Research

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Purpose -The paper's aim is to mine and analyze opinion formation on the basis of consumer dialogs in online forums. Design/methodology/approach -The study identifies opinions, communication relationships, and dialog acts of forum users using different text mining methods. Utilizing this data, social networks can be derived and analyzed to detect influential users and opinion tendencies. The approach is applied to sample online forums discussing the iPhone. Findings -Combining text mining and social network analysis enables the study of opinion formation and yields encouraging results. Out of the four methods employed for text mining, support vector machines performed best.Research limitations/implications -The data set applied here is fairly small. More threads on different products will be considered in future work to improve validation. Practical implications -The approach represents a valuable instrument for online market research. It enables companies to recognize opportunities and risks and to initiate appropriate marketing actions. Originality/value -This work is one of the first studies that combine communication content, relationships and dialog acts for analyzing opinion formation.

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Section: Related Workmentioning

confidence: 99%

Mining consumer dialog in online forums

Kaiser

Bodendorf²

2012

Internet Research

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“…For example, Viermetz et al [56] propose a method for tracking short-term and long-term trends over time. Tong and Yager [54] outline a system which automatically summarizes online discussions.…”

Section: Related Workmentioning

confidence: 99%

Warning system for online market research – Identifying critical situations in online opinion formation

Kaiser

Schlick

Bodendorf

2011

Knowledge-Based Systems

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“…Mei and Zhai also argue that temporal text mining and trend mining have not been well addressed in existing related work and that further research is needed to develop trend mining systems helping users to navigate through large text collections based on temporal trend mining. In contrast, Viermetz et al [51] utilized temporal granularity and a density-based clustering algorithm for extracting short-and long-term topics as keyword vectors. Each topic is described as a keyword vector that is transformed to a representative keyword vector by contrasting the foreground model corpus to a background model.…”

Section: Trend Mining From Textmentioning

confidence: 99%

Visual analytics for technology and innovation management

Nazemi

Burkhardt

Kock

2021

Multimed Tools Appl

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The awareness of emerging trends is essential for strategic decision making because technological trends can affect a firm’s competitiveness and market position. The rise of artificial intelligence methods allows gathering new insights and may support these decision-making processes. However, it is essential to keep the human in the loop of these complex analytical tasks, which, often lack an appropriate interaction design. Including special interactive designs for technology and innovation management is therefore essential for successfully analyzing emerging trends and using this information for strategic decision making. A combination of information visualization, trend mining and interaction design can support human users to explore, detect, and identify such trends. This paper enhances and extends a previously published first approach for integrating, enriching, mining, analyzing, identifying, and visualizing emerging trends for technology and innovation management. We introduce a novel interaction design by investigating the main ideas from technology and innovation management and enable a more appropriate interaction approach for technology foresight and innovation detection.

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Tracking Topic Evolution in News Environments

Cited by 11 publications

References 9 publications

Mining consumer dialog in online forums

Mining consumer dialog in online forums

Warning system for online market research – Identifying critical situations in online opinion formation

Visual analytics for technology and innovation management

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