Comquest: Large Scale User Comment Crawling and Integration

Abstract

User-generated content like comments are valuable sources for various downstream applications. However, access to user comments data is often limited to specific platforms or outlets, which imposes a great limitation on the available data, and may not provide a representative sample of opinions from a diverse population on a particular event. This paper presents a comment crawling system that leverages the Web API of popular third-party commenting systems to collect comments from a large number of websites integrated with the commenting systems. Given a target page, the crawling system utilizes a deep learning model to extract API parameters and send HTTP requests to the API to retrieve comments. The system, Comquest, that we propose to demo is news-oriented and crawls comments regarding specific news topics/stories. Comquest can work with any website that allows commenting. Comquest provides a useful tool for collecting comments that represent a wider range of opinions, stances, and sentiments from websites on a global scale.