INEIS Seminar by Kasper Christensen and Lars Frederiksen

Using human raters, text mining tools and machine learning in your research

2018.05.23 | Merete Elmann

Date Wed 05 Sep
Time 12:00 13:00
Location Room 2628-M211, Department of Management, Aarhus BSS, Aarhus University


Wednesday 5 September 2018 at 12:00 in room 2628-M211, Kasper Christensen, Sr. Data Analyst at Grundfos, and Lars Frederiksen, Professor at Dept. of Management, will give a seminar entitled

Using human raters, text mining tools and machine learning in your research


Everyone is welcome!


Abstract

Online communities are attractive sources of ideas relevant for new product development and innovation. However, making sense of the ‘big data’ in these communities is a complex analytical task. A systematic way of dealing with these data is needed to exploit their potential for boosting companies’ innovation performance. We propose a method for analysing online community data with a special focus on identifying ideas. We employ a research design where two human raters classified 3,000 texts extracted from an online community, according to whether the text contained an idea. Among the 3,000, 137 idea texts and 2,666 non-idea texts were identified. The human raters could not agree on the remaining 197 texts. These texts were omitted from the analysis. The remaining 2,803 texts were processed by using text mining techniques and used to train a classification model. We describe how to tune the model and which text mining steps to perform. We conclude that machine learning and text mining can be useful for detecting ideas in online communities. The method can help researchers and firms identify ideas hidden in large amounts of texts. Also, it is interesting in its own right that machine learning can be used to detect ideas. 


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