Sentiment Analysis: A Multi-Faceted Problem 论文

摘要

Sentiment analysis or opinion mining is the computational study of people’s opinions, appraisals, and emotions toward entities, events and their attributes. In the past few years, it attracted a great deal of attentions from both academia and industry due to many challenging research problems and a wide range of applications [1]. Opinions are important because whenever we need to make a decision we want to hear others’ opinions. This is not only true for individuals but also true for organizations. However, there was almost no computational study on opinions before the Web because there was little opinionated text available. In the past, when an individual needed to make a decision, he/she typically asked for opinions from friends and families. When an organization wanted to find opinions of the general public about its products and services, it conducted surveys and focus groups. However, with the explosive growth of the social media content on the Web in the past few years, the world has been transformed. People can now post reviews of products at merchant sites and express their views on almost anything in discussion forums and blogs, and at social network sites. Now if one wants to buy a product, one is no longer limited to asking one’s friends and families because there are many user reviews on the Web. For a company, it may no longer need to conduct surveys or focus groups in order to gather consumer opinions about its products and those of its competitors because there is a plenty of such information publicly available. However, finding opinion sites and monitoring them on the Web can still be a formidable task because there are a large number of diverse sites, and each site may also have a huge volume of opinionated text. In many cases, opinions are hidden in long forum posts and blogs. It is difficult for a human reader to find relevant sites, extract related sentences with opinions, read them, summarize them, and organize them into usable forms. Automated opinion discovery and summarization systems are thus needed. In this article, I first give a brief introduction to the field and present some technical challenges. We will see that sentiment analysis is not a single task, but a multi-faceted problem containing many subproblems. I will then share some of my thoughts on the past and future of sentiment analysis based on my research in the past few years and my experience in the industry for a short while.