Research outputs per year
Research outputs per year
Project Details
Description
This project investigated Iranian state-sponsored propaganda tweets about the Iranian nuclear deal. More specifically, it investigated the automatic labelling of polarity (positive, neutral, or negative) and the potential to develop machine learning algorithms to detect tweets’ polarity. We also investigated to objectivity of the language used.
Key findings
- In the propaganda tweets, objective language is used as a technique for bringing legitimacy and persuasiveness to the propaganda message.
- The data indicated two possibilities: (1) there are multiple misinformation operations run by different actors with different agendas, or (2) there is one single operation with a strategy of sowing confusion, rather than overtly pursuing a messaging for- or against- the nuclear deal.
- The data indicated two possibilities: (1) there are multiple misinformation operations run by different actors with different agendas, or (2) there is one single operation with a strategy of sowing confusion, rather than overtly pursuing a messaging for- or against- the nuclear deal.
| Status | Finished |
|---|---|
| Effective start/end date | 1/10/20 → 31/08/22 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
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Research output
- 1 Article
-
Sentiment and objectivity in Iranian state-sponsored propaganda on Twitter
Barrows, M., Haig, E. & Conduit, D., 4 Apr 2024, In: IEEE Transactions on Computational Social Systems. 11, 2, p. 2359-2368 10 p.Research output: Contribution to journal › Article › peer-review
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