Topic-Based Sentiment Analysis in Custom...

Much of customer support at LinkedIn is done via some form of online communication such as online feedback forms or email between members and support agents. Topic-based sentiment analysis of member feedback is critical since a single piece of feedback may address several different topics with different sentiment expressed in each. This talk addresses the topic-based sentiment analysis of customer support feedback focusing on the following questions 1) how do we find the most relevant topics of a product in question 2) how do we ensure to attribute sentiment to these specific topics as opposed to the feedback as a whole 3) how do we leverage natural language processing tools such as key phrase extraction and synonym identification to make the obtained topic-sentiment information best suitable for human consumption. The model proposed here is extendable to mining sentiment in reviews or any other sentiment-bearing text.