Was It Worth It? Summarizing and Navigating User Reviews with Natural Language Methods

Gilbert, Eric E.

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https://hdl.handle.net/2142/16363 Copy

Description

Title

Was It Worth It? Summarizing and Navigating User Reviews with Natural Language Methods

Author(s)

Gilbert, Eric E.

Contributor(s)

Karahalios, Karrie

Issue Date

2009-03-31

Keyword(s)

• user reviews
• summarization
• nlp
• social media

Abstract

Popular products often attract an astonishing number of user reviews. Sifting through them by the thousands can be quite a headache, one that has inspired solutions like unique phrase identification (e.g., Yelp) and helpfulness ratings (e.g., Amazon). While clearly useful, these techniques only capitalize on a small subset of the reviews, and cannot an- swer questions like, “do these people care about the same things I care about?” Talking Points is our solution to these problems. It employs natural language methods to summa- rize thousands of user reviews into a navigable, browser- based interface. In addition to describing our novel algo- rithm for feature extraction and sentiment classification, this paper presents the results of an exploratory user study of Talking Points. Our study suggests that users explore reviews far longer with Talking Points than with traditional methods. More surprisingly, in randomized sessions users seemed persuaded to choose those products augmented with Talking Points.

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/16363

Sponsor(s)/Grant Number(s)

• NSF 0643502
• Microsoft

Owning Collections