Want Answers? A Reddit Inspired Study on How to Pose Questions

TL;DR

This study analyzes how social, syntactic, and semantic factors influence the likelihood of questions receiving responses on Reddit, using empirical data and novel factor analysis techniques.

Contribution

It presents the first comprehensive empirical analysis of question factors affecting response rates, utilizing a new Reddit dataset and a sparse nonnegative matrix factorization method.

Findings

Preference-probing questions are less likely to be answered.

Semantic factors can predict response likelihood.

The method captures latent response patterns effectively.

Abstract

Questions form an integral part of our everyday communication, both offline and online. Getting responses to our questions from others is fundamental to satisfying our information need and in extending our knowledge boundaries. A question may be represented using various factors such as social, syntactic, semantic, etc. We hypothesize that these factors contribute with varying degrees towards getting responses from others for a given question. We perform a thorough empirical study to measure effects of these factors using a novel question and answer dataset from the website Reddit.com. To the best of our knowledge, this is the first such analysis of its kind on this important topic. We also use a sparse nonnegative matrix factorization technique to automatically induce interpretable semantic factors from the question dataset. We also document various patterns on response prediction we observe during our analysis in the data. For instance, we found that preference-probing questions are scantily answered. Our method is robust to capture such latent response factors. We hope to make our code and datasets publicly available upon publication of the paper.