Peculiarities of the Correlation between Local and Global News Popularity of Electronic Mass Media

TL;DR

This paper investigates the relationship between local and global news popularity in electronic media, proposing methods to rank documents based on content similarity and temporal factors, and detecting early signs of trending topics.

Contribution

It introduces a novel approach to define and analyze local and global news popularity, along with an algorithm to identify documents gaining popularity before new topics emerge.

Findings

Local and global popularity levels show distinct mutual behaviors.

The proposed algorithm effectively detects documents that become popular prior to new topics.

The approach enhances navigation in information flows by ranking documents based on popularity patterns.

Abstract

One of the approaches to the solution of the navigation problem in current information flows is ranking the documents according to their popularity level. The definition of local and global news popularity which is based on the number of similar-in-content documents, published within local and global time interval, was suggested. Mutual behavior of the documents of local and global popularity levels was studied. The algorithm of detecting the documents which received great popularity before new topics appeared was suggested.