TechScreen Revised

Welcome to TechScreen

Welcome to the TechScreen site. This side shall support the exchange of knowledge in the domain of Web Engineering and related aspects. As a side effect, this side is used for research on knowledge management technologies. User can pose challenges in the problem domain and can participate in quizzes. Further a bibliography about arcticles in different related domains is continously extended. Finally, questionnaires on different issues are provided. To be able to participate you need an account and a password from TU Wien's TISS system.

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Predicting consumer behavior with Web search

Goel S, Hofman JM, Lahaie S, Pennock DM, Watts DJ. 2010. Predicting consumer behavior with Web search. Proceedings of the National academy of sciences. 107:17486–17490.

Submitted by Fabian Eichhorner on Mon, 11/09/2015 - 20:30

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Forecasting Volatility with Empirical Similarity and Google Trends

Hamid A, Heiden M. 2015. Forecasting Volatility with Empirical Similarity and Google Trends. Journal of Economic Behavior & Organization. 117:81.

Submitted by Fabian Eichhorner on Mon, 11/09/2015 - 20:27

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A TAIEX forecasting model based on changes of keyword search volume on Google Trends

Fan M-H, Liao E-C, Chen M-Y. 2014. A TAIEX forecasting model based on changes of keyword search volume on Google Trends. Independent Computing (ISIC), 2014 IEEE International Symposium on. :1–4.

Submitted by Fabian Eichhorner on Mon, 11/09/2015 - 20:24

A General Purpose Model for Future Prediction Based on Web Search Data: Predicting Greek and Spanish Election

Polykalas SE, Prezerakos GN, Konidaris A. 2013. A General Purpose Model for Future Prediction Based on Web Search Data: Predicting Greek and Spanish Election. Advanced Information Networking and Applications Workshops (WAINA), 2013 27th International Conference on. :213–218.

Submitted by Fabian Eichhorner on Mon, 11/09/2015 - 20:04

Using Metrics of Curation to Evaluate Information-Based Ideation

Kerne A., Webb A.M., Smith S.M., Linder R.. 2014. Using Metrics of Curation to Evaluate Information-Based Ideation. Submitted by Diana Paula Costea on Mon, 11/09/2015 - 20:00

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What Happens After the Pin? Examining How Pinterest Influences Users’ Motivation and Behavior

[Anonymous]. 2015. What Happens After the Pin? Examining How Pinterest Influences Users’ Motivation and Behavior Introduction to Social Media Investigation. :pp.115-126.

Submitted by Diana Paula Costea on Mon, 11/09/2015 - 19:42

Pinteresting: Towards a Better Understanding of User Interests

Popescu A-M. 2012. Pinteresting: Towards a Better Understanding of User Interests. Proceedings of the 2012 Workshop on Data-driven User Behavioral Modelling and Mining from Social Media. :11–12.

Submitted by Ana-Maria Patrascu on Mon, 11/09/2015 - 19:32

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TechScreen Revised

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Welcome to TechScreen

The Synergy Between Voting and Acceptance of Answers on StackOverflow, or the Lack thereof

Gender, Representation and Online Participation: A Quantitative Study of StackOverflow

A Hybrid Auto-tagging System for StackOverflow Forum Questions