Identifying Microblogs for Targeted Contextual Advertising

Authors

  • Kushal Dave International Institute of Information Technology, Hyderabad
  • Vasudeva Varma International Institute of Information Technology, Hyderabad

DOI:

https://doi.org/10.1609/icwsm.v6i1.14303

Keywords:

Contextual Advertising, Microblogs, Microposts, classification

Abstract

Micro-blogging sites such as Facebook, Twitter, Google+ present a nice opportunity for targeting advertisements that are contextually related to the microblog content. By virtue of the sparse and noisy text makes identifying the microblogs suitable for advertising a very hard problem. In this work, we approach the problem of identifying the microblogs that could be targeted for advertisements as a two-step classification approach. In the first pass, microblogs suitable for advertising are identified. Next, in the second pass, we build a model to find the sentiment of the advertisable microblog. The systems use features derived from the Part-of-speech tags, the tweet content and uses external resources such as query logs and n-gram dictionaries from previously labeled data.This work aims at providing a thorough insight into the problem and analyzing various features to assess which features contribute the most towards identifying the tweets that can be targeted for advertisements.

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Published

2021-08-03

How to Cite

Dave, K., & Varma, V. (2021). Identifying Microblogs for Targeted Contextual Advertising. Proceedings of the International AAAI Conference on Web and Social Media, 6(1), 431-434. https://doi.org/10.1609/icwsm.v6i1.14303