material ID: twittercorpus

Related Papers

EmpaTweet: Annotating and Detecting Emotions on Twitter

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

AbstractThe rise of micro-blogging in recent years has resulted in significant access to emotion-laden text. Unlike emotion expressed in other textual sources (e.g., blogs, quotes in newswire, email, product reviews, …...

13332

Supervised Text-based Geolocation Using Language Models on an Adaptive Grid

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

The geographical properties of words have re- cently begun to be exploited for geolocating documents based solely on their text, often in the context of social media and online content. …...

44050

That’s So Annoying!!!: A Lexical and Frame-Semantic Embedding Based Data Augmentation Approach to Automatic Categorization of Annoying Behaviors using #petpeeve Tweets

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

We propose a novel data augmentation ap- proach to enhance computational behav- ioral analysis using social media text. In particular, we collect a Twitter corpus of the descriptions of annoying …...

34221

Corpus-Based Diacritic Restoration for South Slavic Languages

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractIn computer-mediated communication, Latin-based scripts users often omit diacritics when writing. Such text is typically easily understandable to humans but very difficult for computational processing because many words become ambiguous …...

15083

Domain Adaptation for Named Entity Recognition Using CRFs

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractIn this paper we explain how we created a labelled corpus in English for a Named Entity Recognition (NER) task from multi-source and multi-domain data, for an industrial partner. We …...

16733

Segmentation-Free Word Embedding for Unsegmented Languages

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractIn this paper, we propose a new pipeline of word embedding for unsegmented languages, called segmentation-free word embedding, which does not require word segmentation as a preprocessing step. Unlike space-delimited …...

33039

An Italian Twitter Corpus of Hate Speech against Immigrants

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

The paper describes a recently-created Twitter corpus of about 6,000 tweets, annotated for hate speech against immigrants, and developed to be a reference dataset for an automatic system of hate …...

17578

Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversations

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractWe study the problem of coarse-grained response selection in retrieval-based dialogue systems. The problem is equally important with fine-grained response selection, but is less explored in existing literature. In this …...

39047

A social media NMT engine for a low-resource language combination

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractThe aim of this article is to present a new Neural Machine Translation (NMT) from Spanish into Galician for the social media domain that was trained with a Twitter corpus. …...

2981

Exploring Amharic Hate Speech Data Collection and Classification Approaches

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractIn this paper, we present a study of efficient data selection and annotation strategies for Amharic hate speech. We also build various classification models and investigate the challenges of hate …...

20155