Work

Barbara Made the News: Mining the Behavior of Crowds for Time-Aware Learning to Rank

Year: 2016

Type: conference-paper

Abstract: In Twitter, and other microblogging services, the generation of new content by the crowd is often biased towards immediacy: what is happening now. Prompted by the propagation of commentary and information through multiple mediums, users on the Web interact with and produce new posts about newsworthy topics and give rise to trending topics. This paper proposes to leverage on the behavioral dynamics of users to estimate the most relevant time periods for a topic. Our hypothesis stems from the fact that when a real-world event occurs it usually has peak times on the Web: a higher volume of tweets, new visits and edits to related Wikipedia articles, and news published about the event.

Source: ACM International Conference on Web Search and Data Mining (WSDM)

DOI: 10.1145/2835776.2835825

Authors: Flávio Martins, João Magalhães, Jamie Callan

Institutions: Universidade Nova de Lisboa, Carnegie Mellon University

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funder: Horizon 2020 Framework Programme

Award: G495187929