Articles
Total Articles: 38870
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14267
AbstractIn this paper we describe and evaluate syntactic and semantic aspects of Arbobanko, a treebank for the artificial language Esperanto, as well as tools and methods used in the production of the treebank. In addition to classical morphosyntax and dependency structure, the treebank was enriched with a lexical-semantic layer covering …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14268
AbstractAs offensive language has become a rising issue for online communities and social media platforms, researchers have been investigating ways of coping with abusive content and developing systems to detect its different types: cyberbullying, hate speech, aggression, etc. With a few notable exceptions, most research on this topic so far …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14269
AbstractThis paper presents the development of a corpus of 30,000 Spanish tweets that were crowd-annotated with humor value and funniness score. The corpus contains approximately 38.6% of humorous tweets with an average score of 2.04 in a scale from 1 to 5 for the humorous tweets. The corpus has been …...
Marking Irony Activators in a Universal Dependencies Treebank: The Case of an Italian Twitter Corpus
14270nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14270
AbstractThe recognition of irony is a challenging task in the domain of Sentiment Analysis, and the availability of annotated corpora may be crucial for its automatic processing. In this paper we describe a fine-grained annotation scheme centered on irony, in which we highlight the tokens that are responsible for its …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14271
AbstractThis paper presents a novel scheme for the annotation of hate speech in corpora of Web 2.0 commentary. The proposed scheme is motivated by the critical analysis of posts made in reaction to news reports on the Mediterranean migration crisis and LGBTIQ+ matters in Malta, which was conducted under the …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14272
AbstractIn this study, we investigate the use of Brown clustering for offensive language detection. Brown clustering has been shown to be of little use when the task involves distinguishing word polarity in sentiment analysis tasks. In contrast to previous work, we train Brown clusters separately on positive and negative sentiment …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14273
AbstractDebate transcripts from the UK Parliament contain information about the positions taken by politicians towards important topics, but are difficult for people to process manually. While sentiment analysis of debate speeches could facilitate understanding of the speakers’ stated opinions, datasets currently available for this task are small when compared to …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14274
AbstractIn this paper we present, describe, and evaluate SentiEcon, a large, comprehensive, domain-specific computational lexicon designed for sentiment analysis applications, for which we compiled our own corpus of online business news. SentiEcon was created as a plug-in lexicon for the sentiment analysis tool Lingmotif, and thus it follows its data …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14275
AbstractReproduction of scientific findings is essential for scientific development across all scientific disciplines and reproducing results of previous works is a basic requirement for validating the hypothesis and conclusions put forward by them. This paper reports on the scientific reproduction of several systems addressing the Argument Reasoning Comprehension Task of …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14276
AbstractDue to the phenomenal growth of online content in recent time, sentiment analysis has attracted attention of the researchers and developers. A number of benchmark annotated corpora are available for domains like movie reviews, product reviews, hotel reviews, etc. The pervasiveness of social media has also lead to a huge …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14277
AbstractThis paper presents the design and construction of a large-scale target-based sentiment annotation corpus on Chinese financial news text. Different from the most existing paragraph/document-based annotation corpus, in this study, target-based fine-grained sentiment annotation is performed. The companies, brands and other financial entities are regarded as the targets. The clause …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14278
AbstractAs a typical multi-layered semi-conscious language phenomenon, sarcasm is widely existed in social media text for enhancing the emotion expression. Thus, the detection and processing of sarcasm is important to social media analysis. However, most existing sarcasm dataset are in English and there is still a lack of authoritative Chinese …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14279
AbstractWe here introduce NoReC_fine, a dataset for fine-grained sentiment analysis in Norwegian, annotated with respect to polar expressions, targets and holders of opinion. The underlying texts are taken from a corpus of professionally authored reviews from multiple news-sources and across a wide variety of domains, including literature, games, music, products, …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14280
AbstractThe sentiment polarity of an expression (whether it is perceived as positive, negative or neutral) can be influenced by a number of phenomena, foremost among them negation. Apart from closed-class negation words like “no”, “not” or “without”, negation can also be caused by so-called polarity shifters. These are content words, …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14281
AbstractIn recent years, sentiment analysis has gained popularity as it is essential to moderate and analyse the information across the internet. It has various applications like opinion mining, social media monitoring, and market research. Aspect Based Sentiment Analysis (ABSA) is an area of sentiment analysis which deals with sentiment at …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14282
AbstractIn this paper, we propose a neural-based model to address the first task of the DEFT 2013 shared task, with the main challenge of a highly imbalanced dataset, using state-of-the-art embedding approaches and deep architectures. We report on our experiments on the use of linguistic features, extracted by Charton et. …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14283
AbstractPolarity classification (positive, negative or neutral opinion detection) is well developed in the field of opinion mining. However, existing tools, which perform with high accuracy on short sentences and explicit expressions, have limited success interpreting narrative phrases and inference contexts. In this article, we will discuss an important aspect of …...
Recommendation Chart of Domains for Cross-Domain Sentiment Analysis: Findings of A 20 Domain Study
14284nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14284
AbstractCross-domain sentiment analysis (CDSA) helps to address the problem of data scarcity in scenarios where labelled data for a domain (known as the target domain) is unavailable or insufficient. However, the decision to choose a domain (known as the source domain) to leverage from is, at best, intuitive. In this …...
Aspect On: an Interactive Solution for Post-Editing the Aspect Extraction based on Online Learning
14285nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14285
AbstractThe task of aspect extraction is an important component of aspect-based sentiment analysis. However, it usually requires an expensive human post-processing to ensure quality. In this work we introduce Aspect On, an interactive solution based on online learning that allows users to post-edit the aspect extraction with little effort. The …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14286
AbstractIn this paper we present the Vaccination Corpus, a corpus of texts related to the online vaccination debate that has been annotated with three layers of information about perspectives: attribution, claims and opinions. Additionally, events related to the vaccination debate are also annotated. The corpus contains 294 documents from the …...