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Annotating Sentiment and Irony in the Online Italian Political Debate on #labuonascuola

Summary

The authors build TW-BS (TWitterBuonaScuola), a new Italian sentiment analysis resource. It focuses on the 2014 Twitter debate over "La Buona Scuola," the Renzi government's controversial school reform. They chose this reform because its hashtag was the most popular of the three big 2014 reform hashtags. They collected tweets using #labuonascuola and related keywords, removed retweets and near-duplicates, and annotated each message for sentiment polarity and irony. The scheme is compatible with the SENTIPOLC format and also labels which aspect (topic) of the reform a tweet addresses. For comparison, they gathered WEB-BS, a set of posts from the government's own online consultation site, which contributors had already tagged with stance and topic. The paper also analyzes inter-annotator disagreement, including tests on the Crowdflower platform. Irony and the neutral NONE label proved hardest to agree on. In TW-BS, negative tweets outnumber positive ones about threefold, and many criticisms are ironic. The consultation posts are more constructive and almost free of irony. The resource supports aspect-level and stance-oriented analysis of political debate.

Key points

  • Twitter data (TW-BS): 35,148 tweets matched the filters for 3 September to 15 November 2014. After automatic and manual deduplication, 8,594 remained.
  • Label distribution in TW-BS:
    • NONE: 3,177
    • NEG: 1,951
    • POS: 756
    • HUM NEG: 655
    • MIX: 92
    • HUM POS: 28
  • Consultation data (WEB-BS): 4,129 posts from labuonascuola.gov.it, labelled by contributors as:
    • 'what I like': 642
    • 'what I don't like': 892
    • 'what is missing': 675
    • 'new integration': 1,920
  • Topic findings: About 80% of the 5,573 topic-agreed tweets received only the generic tag. Topic distributions differ between the sources: evaluation dominates WEB-BS, while recruitment is frequent on Twitter.
  • User activity: In TW-BS, 20% of users produced roughly 60% of tweets, which is less skewed than the 80/20 Pareto pattern.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cited by

12 papers of our library cite it (of the 140673 whose bibliographies we read); 3 of them have a page here, 9 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{stranisci2016annotating,
  title = {{Annotating Sentiment and Irony in the Online Italian Political Debate on \#labuonascuola}},
  author = {Stranisci, Marco and Bosco, Cristina and Farías, Delia Irazú Hernández and Patti, Viviana},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
  year = {2016},
  doi = {10.63317/4abqh39vt3ni},
  url = {https://doi.org/10.63317/4abqh39vt3ni}
}

References

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