Twitter permeability to financial events: an experiment towards a model for sensing irregularities
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2352
- Type
- D - Journal article
- DOI
-
10.1007/s11042-018-6388-4
- Title of journal
- Multimedia Tools and Applications
- Article number
- -
- First page
- 9217
- Volume
- 78
- Issue
- 7
- ISSN
- 1380-7501
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- URL
-
https://e-space.mmu.ac.uk/621082/
- 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)
-
C - Machine Intelligence
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper investigates the permeability of the ‘Twittersphere’ in relation to events within the financial market, scrutinizing the situations where twitter should be considered as a single source of decision making, given the provenance, quality and credibility of tweets. Research was conducted in collaboration with University of Vigo on the creation of a novel fusion ecosystem (Evans et al. 2020; Evans et al. 2021) to detect irregular behaviour in financial markets. Competitive funding was secured through MAGOS (Secure sMArt Grid using Open Source Intelligence).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -