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International Conference on Web Engineering

ICWE 2021: Web Engineering pp 97–112Cite as

Conversation Graphs in Online Social Media

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12706))

Abstract

In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retrieve popular patterns on online conversations using network-based analysis. The analysis consists of two main stages: intent analysis and network generation. Users’ intention is detected using keyword-based categorization of posts and comments, integrated with classification through Naïve Bayes and Support Vector Machine algorithms for uncategorized comments. A continuous human-in-the-loop approach further improves the keyword-based classification. To build and understand communication patterns among the users, we build conversation graphs starting from the hierarchical structure of posts and comments, using a directed multigraph network. The experiments categorize 90% comments with 98% accuracy on a real social media dataset. The model then identifies relevant patterns in terms of shape and content; and finally determines the relevance and frequency of the patterns. Results show that the most popular online discussion patterns obtained from conversation graphs resemble real-life interactions and communication.

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Notes

  1. 1.

    http://www.socialmediaexpo2015.com/yourexpo/.

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Authors and Affiliations

  1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Giuseppe Ponzio, 34, 20133, Milano, Italy

    Marco Brambilla, Alireza Javadian & Amin Endah Sulistiawati

Authors
  1. Marco Brambilla
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  2. Alireza Javadian
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  3. Amin Endah Sulistiawati
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Corresponding author

Correspondence to Marco Brambilla .

Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica, Politecnico di Milano, Milan, Italy

    Marco Brambilla

  2. E2S UPPA, LIUPPA, Université de Pau et des Pays de l’Adour, Anglet, France

    Richard Chbeir

  3. Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands

    Flavius Frasincar

  4. Inria Saclay-Île-de-France, Institut Polytechnique de Paris, Palaiseau, France

    Ioana Manolescu

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Brambilla, M., Javadian, A., Sulistiawati, A.E. (2021). Conversation Graphs in Online Social Media. In: Brambilla, M., Chbeir, R., Frasincar, F., Manolescu, I. (eds) Web Engineering. ICWE 2021. Lecture Notes in Computer Science(), vol 12706. Springer, Cham. https://doi.org/10.1007/978-3-030-74296-6_8

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  • DOI: https://doi.org/10.1007/978-3-030-74296-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-74295-9

  • Online ISBN: 978-3-030-74296-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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