M
Michael Siering
Researcher at Goethe University Frankfurt
Publications - 35
Citations - 1831
Michael Siering is an academic researcher from Goethe University Frankfurt. The author has contributed to research in topics: Financial market & User-generated content. The author has an hindex of 12, co-authored 33 publications receiving 1218 citations.
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Digital Finance and FinTech: current research and future research directions
TL;DR: The Digital Finance Cube as mentioned in this paper is a conceptual basis for reviewing the current state of research in digital finance that deals with these novel and innovative business functions, and it gives an outlook on potential future research directions.
Posted Content
Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions
Florian Glaser,Florian Glaser,Kai Zimmermann,Martin Haferkorn,Moritz Christian Weber,Michael Siering +5 more
TL;DR: Empirical insights are given on whether users’ interest regarding digital currencies is driven by its appeal as an asset or as a currency, finding strong indications that especially uninformed users approaching digital currencies are not primarily interested in an alternative transaction system but seek to participate in anAlternative investment vehicle.
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Explaining and predicting online review helpfulness: The role of content and reviewer-related signals
TL;DR: This research addresses the problem of predicting the helpfulness of online product reviews by developing a comprehensive research model guided by the theoretical foundations of signaling theory and provides evidence that the proposed evaluation scenario provides deeper insights than classical performance metrics.
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Disentangling consumer recommendations: Explaining and predicting airline recommendations based on online reviews
TL;DR: It is shown that service aspect-specific sentiment indicators drive the decision to recommend an airline and that these factors can be incorporated in a predictive model using data mining techniques.
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Detecting Fraudulent Behavior on Crowdfunding Platforms: The Role of Linguistic and Content-Based Cues in Static and Dynamic Contexts
TL;DR: This study analyzes a sample of fraudulent and nonfraudulent projects published at a leading crowdfunding platform and investigates whether content-based cues and linguistic cues are valuable for fraud detection.