An Age has come where online reviews build credibility, whether it's for products, restaurants, companies, or retailers. However, what happens when companies talk up an otherwise poor product by devising a number of enticing fake reviews? Furthermore, what if there were reputation-enhancement services out there that companies can hire to generate deceptive online reviews? Dr. Yejin Choi, Assistant Professor of Computer Science & Engineering at the University of Washington, develops natural language processing (NLP) algorithms to improve the quality of information on the Internet. Dr. Choi was one of the first collaborators to introduce algorithms for detecting deceptive reviews in 2011, which have drawn much attention from both media and academia as well as the law enforcement. This awareness has visibly gained momentum, as the New York law enforcement announced in September, 2013 that it caught and charged 19 firms $350,000 for servicing fake reviews! As she continues her work on detecting subliminal message underlying online text, Dr. Choi expands her influence in exposing fake reviews, predicting the success of novels, and enhancing computer image search.

The human mind tends to focus on a few cues in wordings, while computers can crawl through hundreds of small and big evidences simultaneously and draw correlations between these evidences to make predictions. Devoid of cognitive bias, computers can be trained in a particular domain to decipher distribution and choices of words people use to pick up subtle cues about the intent of the author. Such is the power of NLP algorithms, where the science of artificial intelligence merges with that of human linguistics. With a talented team of Ph.D. students and collaborators across the nation, Dr. Choi harnesses this power to create statistical models that analyze the subtext behind writing styles and enable complex image searches.

Current projects include:

• From Language to the Mind: This project enables computers to read from language to the mind, identifying hidden thoughts and emotions based on diction and syntax. Dr. Choi’s algorithm moves beyond merely detecting deception in online reviews, though; she is working to improve public policy by predicting hygiene inspections using online reviews. When Los Angeles County began requiring restaurants to display their hygiene grades in 1998, the revenues for restaurants with grade A hopped by 5 percent, encouraging owners to maintain a clean environment and dropping hospitalizations for food-borne illnesses by 20 percent. However, hygiene inspection grades are no longer effective in keeping restaurants clean, as the way customers choose where they eat has radically changed due to the rise of online restaurant reviews. These online ratings are based on taste, service, and the overall opinion of an individual customer, which can powerfully and easily render hygiene grades invisible. To this front, Dr. Choi works with collaborators to develop an algorithm that detects keywords in customer reviews that correlate to restaurant hygiene, which will implement a hygiene prediction system for customers to consider.
• Predicting the Success of Novels: Predicting the success of literary works is a curious question among publishers and aspiring writers alike. With collaborators, Dr. Choi is building computer algorithms that can assess writing styles and storylines, to both predict the success of novels and offer feedback to writers. Developing statistical models will help quantify thousands of books, and Dr. Choi has thus far been able to predict literary success with an 84% accuracy. By evolving her algorithms to sort through large-scale, heavy volumes of novels, Dr. Choi hopes to identify key characteristic and stylistic elements that are more prominent in successful writings, and pave the way for assisting writers and publishers.
• From Language to the Visual World: Today, highly multi-modal content inundates the Internet with abundance of images and videos. Visuals have indeed become the most effective way to communicate with users. However, as the demand for visuals continues to grow, the web is becoming less accessible to those visually impaired. In order to provide equal web access, Dr. Choi is designing scalable new machine learning algorithms to translate visual information to non-visual information. As a result, Dr. Choi will facilitate complex image caption generation, using highly expressive and dynamic language instead of a single keyword to describe and find an image. Ultimately, Dr. Choi’s research will aid all users around the nation in accurate image search.