no code implementations • LREC 2022 • Nadhem Zmandar, Tobias Daudert, Sina Ahmadi, Mahmoud El-Haj, Paul Rayson
Natural Language Processing is increasingly being applied in the finance and business industry to analyse the text of many different types of financial documents.
1 code implementation • LREC 2020 • Tobias Daudert
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.
no code implementations • 9 Mar 2020 • Tobias Daudert
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.
no code implementations • SEMEVAL 2019 • Sapna Negi, Tobias Daudert, Paul Buitelaar
We present the pilot SemEval task on Suggestion Mining.
no code implementations • WS 2018 • Tobias Daudert, Paul Buitelaar
Social media{'}s popularity in society and research is gaining momentum and simultaneously increasing the importance of short textual content such as microblogs.
no code implementations • WS 2018 • Tobias Daudert, Paul Buitelaar, Sapna Negi
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.
no code implementations • RANLP 2017 • Tobias Daudert
In today{'}s world, globalisation is not only affecting inter-culturalism but also linking markets across the globe.
no code implementations • SEMEVAL 2017 • Keith Cortis, Andr{\'e} Freitas, Tobias Daudert, Manuela Huerlimann, Manel Zarrouk, H, Siegfried schuh, Brian Davis
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.