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Found 10 papers, 2 papers with code
A Web-based Collaborative Annotation and Consolidation Tool
These downfalls difficult their use in annotation tasks requiring varied text formats, prevent researchers to optimise the tool to the annotation task, and impede people with little programming knowledge to easily modify the tool rendering it unusable for a large cohort.
SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News
This paper discusses the {``}Fine-Grained Sentiment Analysis on Financial Microblogs and News{''} task as part of SemEval-2017, specifically under the {``}Detecting sentiment, humour, and truth{''} theme.
Leveraging News Sentiment to Improve Microblog Sentiment Classification in the Financial Domain
With the rising popularity of social media in the society and in research, analysing texts short in length, such as microblogs, becomes an increasingly important task.
Linking News Sentiment to Microblogs: A Distributional Semantics Approach to Enhance Microblog Sentiment Classification
Social media{'}s popularity in society and research is gaining momentum and simultaneously increasing the importance of short textual content such as microblogs.
Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy
In today{'}s world, globalisation is not only affecting inter-culturalism but also linking markets across the globe.
SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums
We present the pilot SemEval task on Suggestion Mining.
A Multi-Source Entity-Level Sentiment Corpus for the Financial Domain: The FinLin Corpus
We introduce FinLin, a novel corpus containing investor reports, company reports, news articles, and microblogs from StockTwits, targeting multiple entities stemming from the automobile industry and covering a 3-month period.
