Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

12-2013

Abstract

Identifying potential customers among a huge number of users in microblogging is a fundamental problem for microblog marketing. One challenge in potential customer detection in microblogging is how to generate an accurate characteristic description for users, i.e., user profile generation. Intuitively, the preference of a user’s friends (i.e., the person followed by the user in microblogging) is of great importance to capture the characteristic of the user. Also, a user’s self-defined tags are often concise and accurate carriers for the user’s interests. In this paper, for identifying potential customers in microblogging, we propose a method to generate user profiles via a simple integration of social relationship and text data. In particular, our proposed method constructs self-defined tag based user profiles by aggregating tags of the users and their friends. We further identify potential customers among users by using text classification techniques. Although this framework is simple, easy to implement and manipulate, it can obtain desirable potential customer detection accuracy. This is illustrated by extensive experiments on datasets derived from Sina Weibo, the most popular microblogging in China.

Keywords

identifying potential customers, user profile, social relationship, text data, text classification, microblog marketing

Discipline

Databases and Information Systems | Data Storage Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16

Volume

8346

First Page

397

Last Page

409

ISBN

9783642539138

Identifier

10.1007/978-3-642-53914-5_34

Publisher

Springer

City or Country

Hangzhou, China

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