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ITEPE: a source tracing algorithm for the microblog.

Xueyan Zhou1, Jing Yang2, Zehong Lin3

  • 1College of Computer Science and Technology, Harbin Engineering University, Harbin, China; College of Engineering, Harbin University, Harbin, China.

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Summary
This summary is machine-generated.

This study introduces the Initiators and Early Participants Extraction (ITEPE) algorithm to identify the origin of information spread on social media. ITEPE effectively traces information sources by analyzing user interactions and content.

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Area of Science:

  • Social Network Analysis
  • Information Science
  • Computational Social Science

Background:

  • Identifying the origin of information in social networks is vital for understanding information diffusion.
  • Microblogs are a key platform for rapid information dissemination, making source tracing challenging.

Purpose of the Study:

  • To develop and evaluate an algorithm for accurately identifying the initiators and early participants of information cascades on microblogs.
  • To address the problem of social network information tracing using a novel approach.

Main Methods:

  • Constructing information cascades (session trees) based on user retweets.
  • Clustering cascade sets (session forests) by topical relevance.
  • Identifying real initiators via user relationship and information cascade networks.
  • Calculating influence and conformity indices using text sentiment analysis and cascade data.
  • Extracting early important participants based on calculated indices.

Main Results:

  • The proposed Initiators and Early Participants Extraction (ITEPE) algorithm successfully identifies true information sources.
  • Experimental evaluation demonstrates the effectiveness of ITEPE in pinpointing initiators and early participants.
  • The algorithm leverages network structure, user behavior, and content analysis for accurate tracing.

Conclusions:

  • ITEPE provides an effective solution for the crucial task of social network information source tracing.
  • The algorithm's ability to identify initiators and early participants has significant implications for understanding information dynamics.
  • This research contributes a novel methodology for analyzing information diffusion in new media environments.