Abstract
—Background:Onlineforumsareinstrumentsthrough which information or problems are shared and discussed, including expressions of interests and intentions. Objective: In this paper, we present ongoing work aimed at analyzing the content of forum posts of a hybrid open source company that offers both free and commercial licenses, in order to help its community manager gain improved understanding of the forum discussions and sentiments and automatically discover new opportunities such as sales leads, i.e., people who are interested in buying a license. These leads can then be forwarded to the sales team for follow-up and can result in them potentially making a sale, thus increasing company revenue. Method: For the analysis of the forums, an untapped channel for sales leads by the company, text analysis techniques are utilized to identify potential sales leads and the discussion topics and sentiments in those leads. Results: Results of our preliminary work make a positive contribution in lessening the community manager’s work in understanding the sentiment and discussion topics in the hybrid open source forum community, as well as make it easier and faster to identify potential future customers. Conclusion: We believe that the results will positively contribute to improving the sales of licenses for the hybrid open source company
Original language | English |
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Title of host publication | Proceedings - 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2017 : 9-10 November 2017, Toronto, Ontario, Canada |
Publisher | IEEE |
Publication date | 12 Nov 2017 |
Pages | 442-447 |
ISBN (Print) | 978-1-5090-4040-7 |
ISBN (Electronic) | 978-1-5090-4039-1 |
DOIs | |
Publication status | Published - 12 Nov 2017 |
MoE publication type | A4 Article in conference proceedings |
Event | International Symposium on Empirical Software Engineering and Measurement - Toronto, Canada Duration: 9 Nov 2017 → 10 Nov 2017 Conference number: 11 |
Fields of Science
- 113 Computer and information sciences