Search Results for author: Seid Muhie Yimam

Found 26 papers, 5 papers with code

How Hateful are Movies? A Study and Prediction on Movie Subtitles

1 code implementation KONVENS (WS) 2021 Niklas von Boguszewski, Sana Moin, Anirban Bhowmick, Seid Muhie Yimam, Chris Biemann

Hence, we show that transfer learning from the social media domain is efficacious in classifying hate and offensive speech in movies through subtitles.

Domain Adaptation Transfer Learning

ActiveAnno: General-Purpose Document-Level Annotation Tool with Active Learning Integration

no code implementations NAACL 2021 Max Wiechmann, Seid Muhie Yimam, Chris Biemann

ActiveAnno is built with extensible design and easy deployment in mind, all to enable users to perform annotation tasks with high efficiency and high-quality annotation results.

Active Learning

Word Complexity is in the Eye of the Beholder

no code implementations NAACL 2021 Sian Gooding, Ekaterina Kochmar, Seid Muhie Yimam, Chris Biemann

Lexical complexity is a highly subjective notion, yet this factor is often neglected in lexical simplification and readability systems which use a {''}one-size-fits-all{''} approach.

Lexical Simplification

SCoT: Sense Clustering over Time: a tool for the analysis of lexical change

no code implementations EACL 2021 Christian Haase, Saba Anwar, Seid Muhie Yimam, Alexander Friedrich, Chris Biemann

There are two main approaches to the exploration of dynamic networks: the discrete one compares a series of clustered graphs from separate points in time.

HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection

4 code implementations18 Dec 2020 Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, Animesh Mukherjee

We also observe that models, which utilize the human rationales for training, perform better in reducing unintended bias towards target communities.

Hate Speech Detection Text Classification

Exploring Amharic Sentiment Analysis from Social Media Texts: Building Annotation Tools and Classification Models

no code implementations COLING 2020 Seid Muhie Yimam, Hizkiel Mitiku Alemayehu, Abinew Ayele, Chris Biemann

To advance the sentiment analysis research in Amharic and other related low-resource languages, we release the dataset, the annotation tool, source code, and models publicly under a permissive.

Decision Making Sentiment Analysis

Analysis of the Ethiopic Twitter Dataset for Abusive Speech in Amharic

no code implementations9 Dec 2019 Seid Muhie Yimam, Abinew Ali Ayele, Chris Biemann

Since several languages can be written using the Fidel script, we have used the existing Amharic, Tigrinya and Ge'ez corpora to retain only the Amharic tweets.

A Multilingual Information Extraction Pipeline for Investigative Journalism

no code implementations EMNLP 2018 Gregor Wiedemann, Seid Muhie Yimam, Chris Biemann

We introduce an advanced information extraction pipeline to automatically process very large collections of unstructured textual data for the purpose of investigative journalism.

Entity Extraction using GAN

New/s/leak 2.0 - Multilingual Information Extraction and Visualization for Investigative Journalism

no code implementations13 Jul 2018 Gregor Wiedemann, Seid Muhie Yimam, Chris Biemann

Investigative journalism in recent years is confronted with two major challenges: 1) vast amounts of unstructured data originating from large text collections such as leaks or answers to Freedom of Information requests, and 2) multi-lingual data due to intensified global cooperation and communication in politics, business and civil society.

Efficient Exploration

Par4Sim -- Adaptive Paraphrasing for Text Simplification

no code implementations COLING 2018 Seid Muhie Yimam, Chris Biemann

Learning from a real-world data stream and continuously updating the model without explicit supervision is a new challenge for NLP applications with machine learning components.

Learning-To-Rank Text Simplification

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