Information Spread in a Connected World

TL;DR

This paper compares word-of-mouth and search engine-based information spread, proposing a new theoretical model that considers search engines as central hubs influencing how opinions form and evolve in a connected world.

Contribution

It introduces a novel theoretical perspective on information dissemination that incorporates search engine dynamics and evaluates their impact on collective knowledge.

Findings

Search engines act as central hubs connecting users to information.

Overuse of search engines may narrow the collective information set.

Theoretical models suggest thresholds influence opinion adoption.

Abstract

In the following work, we compare the spread of information by word-of-mouth (WOM) to the spread of information through search engines. We assume that the initial acknowledgement of new information derives from social interactions but that solid opinions are only formed after further evaluation through search engines. Search engines can be viewed as central hubs that connect information presented in relevant websites to searchers. Since they construct new connections between searchers and information in every query performed, the network structure is less relevant. Although models of viral spread of ideas have been inspected in many previous works [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], only few assume the acceptance of a novel concept to be solely based on the evaluation of the opinions of others [8], [5]. Following this approach, combined with that of models of information spread with threshold [1] that claim the propagation in a network to occur only if a threshold of neighbors hold an opinion, the proposed work adds a new theoretical perspective that is relevant to the daily use of search engines as a major information search tool. We continue by presenting some justifications based on experimentations. Last we discuss possible outcomes of over use of search engines vs. WOM, and suggest an hypothesis that such overuse might actually narrow the collective information set.