2 research outputs found
ANDES at SemEval-2020 Task 12: A jointly-trained BERT multilingual model for offensive language detection
This paper describes our participation in SemEval-2020 Task 12: Multilingual
Offensive Language Detection. We jointly-trained a single model by fine-tuning
Multilingual BERT to tackle the task across all the proposed languages:
English, Danish, Turkish, Greek and Arabic. Our single model had competitive
results, with a performance close to top-performing systems in spite of sharing
the same parameters across all languages. Zero-shot and few-shot experiments
were also conducted to analyze the transference performance among these
languages. We make our code public for further researchComment: Github repo: https://github.com/finiteautomata/offenseval202
Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research
Sentiment analysis as a field has come a long way since it was first
introduced as a task nearly 20 years ago. It has widespread commercial
applications in various domains like marketing, risk management, market
research, and politics, to name a few. Given its saturation in specific
subtasks -- such as sentiment polarity classification -- and datasets, there is
an underlying perception that this field has reached its maturity. In this
article, we discuss this perception by pointing out the shortcomings and
under-explored, yet key aspects of this field that are necessary to attain true
sentiment understanding. We analyze the significant leaps responsible for its
current relevance. Further, we attempt to chart a possible course for this
field that covers many overlooked and unanswered questions.Comment: Published in the IEEE Transactions on Affective Computing (TAFFC