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Conference object . 2023
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https://doi.org/10.18653/v1/20...
Article . 2023 . Peer-reviewed
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Article . 2023
License: CC BY
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https://dx.doi.org/10.60692/7y...
Other literature type . 2023
Data sources: Datacite
https://dx.doi.org/10.60692/2p...
Other literature type . 2023
Data sources: Datacite
http://dx.doi.org/10.18653/v1/...
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SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)

SemEval -2023 المهمة 12: تحليل المشاعر للغات الأفريقية (AfriSenti - SemEval)
Authors: Shamsuddeen Hassan Muhammad; Idris Abdulmumin; Seid Muhie Yimam; David Ifeoluwa Adelani; Ibrahim Said Ahmad; Nedjma Ousidhoum; Abinew Ali Ayele; +3 Authors

SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)

Abstract

We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEval is a sentiment classification challenge in 14 African languages: Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yorùbá (Muhammad et al., 2023), using data labeled with 3 sentiment classes. We present three subtasks: (1) Task A: monolingual classification, which received 44 submissions; (2) Task B: multilingual classification, which received 32 submissions; and (3) Task C: zero-shot classification, which received 34 submissions. The best performance for tasks A and B was achieved by NLNDE team with 71.31 and 75.06 weighted F1, respectively. UCAS-IIE-NLP achieved the best average score for task C with 58.15 weighted F1. We describe the various approaches adopted by the top 10 systems and their approaches.

19 pages, 5 figures, 6 tables

Keywords

FOS: Computer and information sciences, Artificial intelligence, Språkbehandling och datorlingvistik, Discourse Analysis, Economics, Social Sciences, NLP, Language and Linguistics, Language Technology (Computational Linguistics), Sentiment analysis, Task (project management), Low Resource, Artificial Intelligence, Sentiment Analysis, Språkteknologi (språkvetenskaplig databehandling), Natural Language Processing, Studier av enskilda språk, Computer Science - Computation and Language, Natural language processing, Language Studies and Linguistics Research, Computer science, Specific Languages, Management, Sentiment Analysis and Opinion Mining, AfriSenti, Computer Science, Physical Sciences, Arts and Humanities, Computation and Language (cs.CL), SemEval

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Top 10%
Top 10%
Green
bronze