iStory: intelligent storytelling with social data

Amin Beheshti*, Alireza Tabebordbar, Boualem Benatallah

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

16 Citations (Scopus)
212 Downloads (Pure)


The production of knowledge from ever increasing amount of social data is seen by many organizations as an increasingly important capability that can complement the traditional analytics sources. Examples include extracting knowledge and deriving insights from social data to improve government services, predict intelligence activities, personalize the advertisements in elections and improve national security and public health. Understanding social data can be challenging as the analysis goal can be subjective. In this context, storytelling is considered as an appropriate metaphor as it facilitates understanding and surfacing insights which is embedded within the data. In this paper, we focus on the research problem of ‘understanding the social data’ in general and more particularly the curation, summarization and presentation of large amounts of social data. The goal is to enable intelligent narrative construction based on the important features (extracted and ranked automatically) and enable storytelling at multiple levels and from different views using novel summarization techniques. We implement an interactive storytelling dashboard, namely iStory, and focus on a motivating scenario for analyzing Urban Social Issues from Twitter as it relates to the Australian Government Budget, to highlight how storytelling can significantly facilitate understanding social data.
Original languageEnglish
Title of host publicationThe Web Conference 2020
Subtitle of host publicationCompanion of the World Wide Web Conference WWW 2020
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Electronic)9781450370240
Publication statusPublished - Apr 2020
EventThe Web Conference (29th : 2020)
- Taipei, Taiwan
Duration: 20 Apr 202024 Apr 2020

Publication series

NameThe World Wide Web (WWW) Conference


ConferenceThe Web Conference (29th : 2020)

Bibliographical note

Copyright the Publisher 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • Data Curation
  • Data Lake
  • Knowledge Lake
  • Storytelling
  • Summarization


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