The steps involved in sentiment analysis are easy enough to grasp: use automated tools to discern, extract, and process attitudinal information found in text; apply to sources as varied as articles, blog postings, e-mail, call-center notes, and survey responses that capture facts and opinions. What do customers, reviewers, the business community – thought leaders and the public – think about your company and your company's products and services – and about your competitors? What can you learn that will help you improve design and quality, positioning, and messaging and also respond quickly to complaints?
The goal is to create market intelligence, to identify opportunities and issues, to understand the voice of the customer as expressed in everyday communications. The challenge stems from the huge variability and subtlety of spoken and written language: meaning that humans readily grasp from context is very difficult for computers to detect. How can software reliably discern facts and feelings in light of not only abbreviations, bad spelling, and fractured grammar, but also sarcasm, irony, slang, idiom, and, well, personality? How is a computer to understand? The following is taken verbatim from Dell's IdeaStorm.com, complete with misspellings and a buried subject, RAM – “Dell really... REALLY need to stop overcharging... and when i say overcharing... i mean atleast double what you would pay to pick up the ram yourself. ” (Isn't it excellent that Dell openly solicits customer feedback?) How can software additionally judge the impact of a posting like this? It's a hard challenge, yet the potential return is huge, as is the risk of not trying. 数据挖掘研究院
Text analytics can extend reach, lower costs, and improve reaction time in dealing with important enterprise information, including sentiment, that is locked in a variety of forms of human communications. Workers have limited capacity and they're (relatively) expensive, so we use computers for what they're good at: processing large volumes of data fast. Yet accuracy is a serious concern, and there is wide variation in the suitability of various available tools to the task. It is important to know what you can expect in order to create an approach that works given your information sources and goals.
