Tracking the Diffusion of Named Entities
Leon Derczynski, Matthew Rowe

TL;DR
This paper explores how real-world entities spread on social media, particularly Reddit, by developing methods for entity recognition and a diffusion model that predicts entity adoption based on user interactions.
Contribution
It introduces a novel approach to extract and analyze the diffusion of named entities on social media, with a parallelized model for forecasting entity adoption.
Findings
Entity adoption influenced by prior user interactions
Proposed diffusion model accurately forecasts entity spread
Highlights importance of interaction history over propagation history
Abstract
Existing studies of how information diffuses across social networks have thus far concentrated on analysing and recovering the spread of deterministic innovations such as URLs, hashtags, and group membership. However investigating how mentions of real-world entities appear and spread has yet to be explored, largely due to the computationally intractable nature of performing large-scale entity extraction. In this paper we present, to the best of our knowledge, one of the first pieces of work to closely examine the diffusion of named entities on social media, using Reddit as our case study platform. We first investigate how named entities can be accurately recognised and extracted from discussion posts. We then use these extracted entities to study the patterns of entity cascades and how the probability of a user adopting an entity (i.e. mentioning it) is associated with exposures to the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Spam and Phishing Detection
