Статьи

In this paper, we present Arap-Tweet, which is a large-scale and multi-dialectal corpus of Tweets from 11 regions and 16 countries in the Arab world representing the major Arabic dialectal varieties. To build this corpus, we collected data from Twitter and we provided a team of experienced annotators with annotation …...

In this paper, we describe a study we conducted to determine, if a person who is highly influential in a discussion on a familiar topic would retain influence when moving to a topic that is less familiar or perhaps not as interesting. For this research, we collected samples of realistic …...

In this work we present a taxonomy of error categories for lexical normalization, which is the task of translating user generated content to canonical language. We annotate a recent normalization dataset to test the practical use of the taxonomy and read a near-perfect agreement. This annotated dataset is then used …...

Extracting semi-structured text from scientific writing in PDF files is a difficult task that researchers have faced for decades. In the 1990s, this task was largely a computer vision and OCR problem, as PDF files were often the result of scanning printed documents. Today, PDFs have standardized digital typesetting without …...

Emoji are pictographs commonly used in microblogs as emotion markers, but they can also represent a much wider range of concepts. Additionally, they may occur in different positions within a message (e.g. a tweet), appear in sequences or act as word substitute. Emoji must be considered necessary elements in the …...

We address the problem of mining code-switched data from the web, where code-switching is defined as the tendency of bilinguals to switch between their multiple languages both across and within utterances. We propose a method that identifies data as code-switched in languages L1 and L2 when a language classifier labels …...

Off-the-shelf part-of-speech taggers typically perform relatively poorly on web and social media texts since those domains are quite different from the newspaper articles on which most tagger models are trained. In this paper, we describe SoMeWeTa, a part-of-speech tagger based on the averaged structured perceptron that is capable of domain …...

The rich user-generated content found on internet blogs have always attracted the interest of scientific communities for many different purposes, such as from opinion and sentiment mining, information extraction or topic discovery. Nonetheless, an extensive corpora is essential to perform most of Natural Language Processing involved in these tasks. This …...

While sentiment analysis has become an established field in the NLP community, research into languages other than English has been hindered by the lack of resources. Although much research in multi-lingual and cross-lingual sentiment analysis has focused on unsupervised or semi-supervised approaches, these still require a large number of resources …...

The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users’ daily lives by steering them towards behaviors that …...

We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for sarcasm research and for training and evaluating systems for sarcasm detection. The corpus has 1.3 million sarcastic statements — 10 times more than any previous dataset — and many times more instances of non-sarcastic statements, allowing for learning in …...

This paper describes a language-independent model for multi-class sentiment analysis using a simple neural network architecture of five layers (Embedding, Conv1D, GlobalMaxPooling and two Fully-Connected). The advantage of the proposed model is that it does not rely on language-specific features such as ontologies, dictionaries, or morphological or syntactic pre-processing. Equally …...

Understanding the polarity or sentiment of a text is an important task in many application scenarios. Sentiment Analysis of a text can be used to answer various questions such as election prediction, favouredness towards any product etc. But the sentiment analysis task becomes challenging when it comes to low resource …...

We propose a novel bootstrapping approach for the acquisition of lexicons from unannotated, informal online texts (in our case, Yelp reviews) for polar-opposite emotion dimension values from the Ortony/Clore/Collins model of emotions (e.g., desirable/undesirable). Our approach mitigates the intrinsic problem of limited supervision in bootstrapping with an effective strategy that …...

Negation is an important contextual phenomenon that needs to be addressed in sentiment analysis. Next to common negation function words, such as not or none, there is also a considerably large class of negation content words, also referred to as shifters, such as the verbs diminish, reduce or reverse. However, …...

We report a highly accurate hypernym discovery heuristic that works on unrestricted texts. This approach leverages morphological cues in French, but given any parallel data and word alignment tool, this proves to be a technique that can work reliably in other languages as well. We tested this method using two …...

This paper faces the problem of unifying the representation of actions and events in different semantic resources. The proposed solution exploits the IMAGACT visual component (video scenes that represent physical actions) as the linkage point among resources. By using visual objects, we connected resources responding to different scopes and theoretical …...

This paper presents our work dealing with a potential application in e-lexicography: the automatized creation of specialized multilingual dictionaries from structured data, which are available in the form of comparable multilingual classification schemes or taxonomies. As starting examples, we use comparable industry classification schemes, which frequently occur in the context …...

We introduce a new lexical resource that enriches the Framester knowledge graph, which links Framnet, WordNet, VerbNet and other resources, with semantic features from text corpora. These features are extracted from distributionally induced sense inventories and subsequently linked to the manually-constructed frame representations to boost the performance of frame disambiguation …...

Scholars and their academic information are widely distributed on the Web. Integrating these information and making association between them can play a catalytic role in academic evaluation and research. Since 2008, Web and Mobile Data Management Laboratory (WAMDM) in Renmin University of China began to collect Chinese literatures in more …...