Abstract
Social network analysis has received much attention from corporations recently. Corporations are trying to utilize social media platforms such as Twitter, Facebook and Sina Weibo to expand their own markets. Our system is an online tool to assist these corporations to 1) find potential customers, and 2) track a list of users by specific events from social networks. We employ both textual and network information, and thus produce a keyword-based relevance score for each user in pre-defined dimensions, which indicates the probability of the adoption of a product. Based on the score and its trend, out tool is able to pick up the potential customers for different kinds of products, such as suits which are time-insensitive and diapers which are time-sensitive. In order to detect the scenario of purchasing products as gifts, we filter the user network and only consider the off-line close friend network. In addition, we could track users in a more flexible way. Despite the pre-defined dimensions, our tool is also able to track users by customized events and catch those who mention the event at an early stage.
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These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2013 Springer International Publishing Switzerland
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Du, J., Tan, B., Zhu, F., Lim, EP. (2013). Social Listening for Customer Acquisition. In: Jatowt, A., et al. Social Informatics. SocInfo 2013. Lecture Notes in Computer Science, vol 8238. Springer, Cham. https://doi.org/10.1007/978-3-319-03260-3_7
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DOI: https://doi.org/10.1007/978-3-319-03260-3_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03259-7
Online ISBN: 978-3-319-03260-3
eBook Packages: Computer ScienceComputer Science (R0)