Semantics-Space-Time Cube: A Conceptual Framework for Systematic Analysis of Texts in Space and Time
- Submitting institution
-
City, University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 801
- Type
- D - Journal article
- DOI
-
10.1109/TVCG.2018.2882449
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 1789
- Volume
- 26
- Issue
- 4
- ISSN
- 1077-2626
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 14
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Output presents a novel approach to extracting topics from text and also identifying changes over time. It is published in the most important journal in its domain and was presented at IEEE VIS (A CORE), Vancouver, 2019, the world-leading visualisation conference - acceptance 25%. The presented research extends earlier work that received the Best Paper award at EuroVA (2018); was developed through several large-scale projects on social media analysis funded by the EU, German Research Foundation, and Chinese government; and provided a basis for EU-funded projects, including SoBigData (654024) and SoBigData++ (871042) and Track&Know (780754).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
