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Detection and Resolution of Rumours in Social Media
TLDR
This article introduces and discusses two types of rumours that circulate on social media: long-standing rumours that circulating for long periods of time, and newly emerging rumours spawned during fast-paced events such as breaking news, where reports are released piecemeal and often with an unverified status in their early stages. Expand
Extracting bilingual terminologies from comparable corpora
TLDR
This paper treats bilingual term extraction as a classification problem and uses an SVM binary classifier and training data taken from the EUROVOC thesaurus for classification and performs manual evaluation on bilingual terms extracted from English-German term-tagged comparable corpora. Expand
The challenging task of summary evaluation: an overview
TLDR
A clear up-to-date overview of the evolution and progress of summarization evaluation is provided, giving the reader useful insights into the past, present and latest trends in the automatic evaluation of summaries. Expand
What works and what does not: Classifier and feature analysis for argument mining
TLDR
Although the performance of classifiers varies depending on the feature combinations and corpora used for training and testing, Random Forest seems to be among the best performing classifiers. Expand
Can Rumour Stance Alone Predict Veracity?
TLDR
This paper demonstrates that HMMs that use stance and tweets’ times as the only features for modelling true and false rumours achieve F1 scores in the range of 80%, outperforming those approaches where stance is used jointly with content and user based features. Expand
Simple Open Stance Classification for Rumour Analysis
TLDR
A surprisingly simple and efficient classification approach to open stance classification in Twitter, for rumour and veracity classification, which profits from a novel set of automatically identifiable problem-specific features. Expand
A Collection of Comparable Corpora for Under-resourced Languages
TLDR
Criteria and metrics of comparability will be applied to comparable texts to determine their suitability for use in Statistical Machine Translation, particularly in the case where translation is performed from or into under-resourced languages for which substantial parallel corpora are unavailable. Expand
Analyzing the capabilities of crowdsourcing services for text summarization
TLDR
This paper presents a detailed analysis of the use of crowdsourcing services for the Text Summarization task in the context of the tourist domain and serves as a guideline for the types of experiments that might or might not work when using crowdsourcing in the contexts of text summarization. Expand
The SENSEI Annotated Corpus: Human Summaries of Reader Comment Conversations in On-line News
TLDR
A method is described to support humans in authoring conversation overview summaries and a publicly available corpus is presented – the first of its kind – of news articles plus comment sets, each multiply annotated, according to the method, with conversation Overview summaries. Expand
Generating Image Descriptions Using Dependency Relational Patterns
TLDR
The results show that summaries biased by dependency pattern models lead to significantly higher ROUGE scores than both n-gram language models reported in previous work and also Wikipedia baseline summaries. Expand
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