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Identifying opinion leaders in the blogosphere

Published: 06 November 2007 Publication History

Abstract

Opinion leaders are those who bring in new information, ideas, and opinions, then disseminate them down to the masses, and thus influence the opinions and decisions of others by a fashion of word of mouth. Opinion leaders capture the most representative opinions in the social network, and consequently are important for understanding the massive and complex blogosphere. In this paper, we propose a novel algorithm called InfluenceRank to identify opinion leaders in the blogosphere. The InfluenceRank algorithm ranks blogs according to not only how important they are as compared to other blogs, but also how novel the information they can contribute to the network. Experimental results indicate that our proposed algorithm is effective in identifying influential opinion leaders.

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cover image ACM Conferences
CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
November 2007
1048 pages
ISBN:9781595938039
DOI:10.1145/1321440
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 November 2007

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Author Tags

  1. blog ranking
  2. network summarization
  3. opinion leader

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  • (2024)Identification of Social Network Opinion Leaders Based on Multi-Attribute Decision MakingOperations Research and Fuzziology10.12677/orf.2024.14215914:02(547-555)Online publication date: 2024
  • (2024)Status-Aware Signed Heterogeneous Network Embedding With Graph Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.3151046(1-13)Online publication date: 2024
  • (2024)A novel synthetical hierarchical community paradigm for social network division from the perspective of information ecosystemTechnology in Society10.1016/j.techsoc.2024.102784(102784)Online publication date: Dec-2024
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