Extracting content holes by comparing community‐type content with Wikipedia

Abstract

PurposeCommunity‐type content that are social network services and blogs are maintained by communities of people. Occasionally, community members do not understand the nature of the content from multiple perspectives, and so the volume of information is often inadequate. The authors thus consider it necessary to present users with missing information. The purpose of this paper is to search for the content “hole” where users of community‐type content missed information.Design/methodology/approachThe proposed content hole is defined as different information that is obtained by comparing community‐type content with other content, such as other community‐type content, other conventional web content, and real‐world content. The paper suggests multiple types of content holes and proposes a system that compares community‐type content with Wikipedia articles and identifies the content hole. The paper first identifies structured keywords from the community‐type content, and extracts target articles from Wikipedia using the keywords. It then extracts other related articles from Wikipedia using the link graph. Finally, it compares community‐type content with the articles in Wikipedia and extracts and presents content holes.FindingsInformation retrieval looks for similar data. In contrast, a content‐hole search looks for information that is different. This paper defines the type of content hole on the basis of viewpoints. The proposed viewpoints are coverage, detail, semantics, and reputation.Originality/valueThe paper proposes a system for extracting coverage content holes. The system compares community‐type content with Wikipedia and extracts content holes in the community‐type content.