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Found 95 papers, 3 papers with code
Discovering Financial Hypernyms by Prompting Masked Language Models
With the rising popularity of Transformer-based language models, several studies have tried to exploit their masked language modeling capabilities to automatically extract relational linguistic knowledge, although this kind of research has rarely investigated semantic relations in specialized domains.
ROCLING-2021 Shared Task: Dimensional Sentiment Analysis for Educational Texts
This paper presents the ROCLING 2021 shared task on dimensional sentiment analysis for educational texts which seeks to identify a real-value sentiment score of self-evaluation comments written by Chinese students in the both valence and arousal dimensions.
Decoding Word Embeddings with Brain-Based Semantic Features
For each probing task, we identify the most relevant semantic features and we show that there is a correlation between the embedding performance and how they encode those features.
Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese
Recent research has brought a wind of using computational approaches to the classic topic of semantic change, aiming to tackle one of the most challenging issues in the evolution of human language.
Is Domain Adaptation Worth Your Investment? Comparing BERT and FinBERT on Financial Tasks
With the recent rise in popularity of Transformer models in Natural Language Processing, research efforts have been dedicated to the development of domain-adapted versions of BERT-like architectures.
Inclusion in CSR Reports: The Lens from a Data-Driven Machine Learning Model
Inclusion, as one of the foundations in the diversity, equity, and inclusion initiative, concerns the degree of being treated as an ingroup member in a workplace.
Framing Legitimacy in CSR: A Corpus of Chinese and American Petroleum Company CSR Reports and Preliminary Analysis
The BUILDING source domain was used more often as gain frames in both Chinese and American CSR reports to show how oil companies create benefits for different stakeholders.
Scikit-talk: A toolkit for processing real-world conversational speech data
We present Scikit-talk, an open-source toolkit for processing collections of real-world conversational speech in Python.
Cross-strait Variations on Two Near-synonymous Loanwords xie2shang1 and tan2pan4: A Corpus-based Comparative Study
This study attempts to investigate cross-strait variations on two typical synonymous loanwords in Chinese, i. e. xie2shang1 and tan2pan4, drawn on MARVS theory.
Automatic Analysis of Linguistic Features in Journal Articles of Different Academic Impacts with Feature Engineering Techniques
This study attempts to extract micro-level linguistic features in high- and moderate-impact journal RAs, using feature engineering methods.
PolyU CBS-Comp at SemEval-2021 Task 1: Lexical Complexity Prediction (LCP)
In this contribution, we describe the system presented by the PolyU CBS-Comp Team at the Task 1 of SemEval 2021, where the goal was the estimation of the complexity of words in a given sentence context.
Predicting gender and age categories in English conversations using lexical, non-lexical, and turn-taking features
We explore differences in language use and turn-taking dynamics and identify a range of characteristics that set the categories apart.
Comparing Probabilistic, Distributional and Transformer-Based Models on Logical Metonymy Interpretation
In linguistics and cognitive science, Logical metonymies are defined as type clashes between an event-selecting verb and an entity-denoting noun (e. g.
Sina Mandarin Alphabetical Words:A Web-driven Code-mixing Lexical Resource
Mandarin Alphabetical Word (MAW) is one indispensable component of Modern Chinese that demonstrates unique code-mixing idiosyncrasies influenced by language exchanges.
Automatic Learning of Modality Exclusivity Norms with Crosslingual Word Embeddings
Our experiments focused on crosslingual word embeddings, in order to predict modality association scores by training on a high-resource language and testing on a low-resource one.
Using Conceptual Norms for Metaphor Detection
This paper reports a linguistically-enriched method of detecting token-level metaphors for the second shared task on Metaphor Detection.
Affection Driven Neural Networks for Sentiment Analysis
Deep neural network models have played a critical role in sentiment analysis with promising results in the recent decade.
Are Word Embeddings Really a Bad Fit for the Estimation of Thematic Fit?
While neural embeddings represent a popular choice for word representation in a wide variety of NLP tasks, their usage for thematic fit modeling has been limited, as they have been reported to lag behind syntax-based count models.
Ciron: a New Benchmark Dataset for Chinese Irony Detection
Automatic Chinese irony detection is a challenging task, and it has a strong impact on linguistic research.
Distributional Semantics Meets Construction Grammar. towards a Unified Usage-Based Model of Grammar and Meaning
In this paper, we propose a new type of semantic representation of Construction Grammar that combines constructions with the vector representations used in Distributional Semantics.
A Structured Distributional Model of Sentence Meaning and Processing
In this paper, we propose a Structured Distributional Model (SDM) that combines word embeddings with formal semantics and is based on the assumption that sentences represent events and situations.
A Report on the Third VarDial Evaluation Campaign
In this paper, we present the findings of the Third VarDial Evaluation Campaign organized as part of the sixth edition of the workshop on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects (VarDial), co-located with NAACL 2019.
A realistic and robust model for Chinese word segmentation
Both experiments support the claim that the WBD model is a realistic model for Chinese word segmentation as it can be easily adapted for new variants with the robust result.
Dual Memory Network Model for Biased Product Review Classification
In this work, we propose a dual user and product memory network (DUPMN) model to learn user profiles and product reviews using separate memory networks.
Ranked #6 on
Sentiment Analysis
on User and product information
Fake News Detection Through Multi-Perspective Speaker Profiles
This paper proposes a novel method to incorporate speaker profiles into an attention based LSTM model for fake news detection.
A Cognition Based Attention Model for Sentiment Analysis
Evaluations show the CBA based method outperforms the state-of-the-art local context based attention methods significantly.
Leveraging Eventive Information for Better Metaphor Detection and Classification
We propose a set of syntactic conditions crucial to event structures to improve the model based on the classification of radical groups.
Selective Annotation of Sentence Parts: Identification of Relevant Sub-sentential Units
Many NLP tasks involve sentence-level annotation yet the relevant information is not encoded at sentence level but at some relevant parts of the sentence.
Testing APSyn against Vector Cosine on Similarity Estimation
In Distributional Semantic Models (DSMs), Vector Cosine is widely used to estimate similarity between word vectors, although this measure was noticed to suffer from several shortcomings.
Representing Verbs with Rich Contexts: an Evaluation on Verb Similarity
Several studies on sentence processing suggest that the mental lexicon keeps track of the mutual expectations between words.
Database of Mandarin Neighborhood Statistics
In the design of controlled experiments with language stimuli, researchers from psycholinguistic, neurolinguistic, and related fields, require language resources that isolate variables known to affect language processing.
EVALution-MAN: A Chinese Dataset for the Training and Evaluation of DSMs
In the 360 word relation pairs, there are 373 relata.
A lexicon of perception for the identification of synaesthetic metaphors in corpora
Synaesthesia is a type of metaphor associating linguistic expressions that refer to two different sensory modalities.
Unsupervised Measure of Word Similarity: How to Outperform Co-occurrence and Vector Cosine in VSMs
In this paper, we claim that vector cosine, which is generally considered among the most efficient unsupervised measures for identifying word similarity in Vector Space Models, can be outperformed by an unsupervised measure that calculates the extent of the intersection among the most mutually dependent contexts of the target words.
ROOT13: Spotting Hypernyms, Co-Hyponyms and Randoms
In this paper, we describe ROOT13, a supervised system for the classification of hypernyms, co-hyponyms and random words.
What a Nerd! Beating Students and Vector Cosine in the ESL and TOEFL Datasets
In this paper, we claim that Vector Cosine, which is generally considered one of the most efficient unsupervised measures for identifying word similarity in Vector Space Models, can be outperformed by a completely unsupervised measure that evaluates the extent of the intersection among the most associated contexts of two target words, weighting such intersection according to the rank of the shared contexts in the dependency ranked lists.
Nine Features in a Random Forest to Learn Taxonomical Semantic Relations
When the classification is binary, ROOT9 achieves the following results against the baseline: hypernyms-co-hyponyms 95. 7% vs. 69. 8%, hypernyms-random 91. 8% vs. 64. 1% and co-hyponyms-random 97. 8% vs. 79. 4%.
Annotating Events in an Emotion Corpus
This paper presents the development of a Chinese event-based emotion corpus.
Event Structure of Transitive Verb: A MARVS perspective
Module-Attribute Representation of Verbal Semantics (MARVS) is a theory of the representation of verbal semantics that is based on Mandarin Chinese data (Huang et al. 2000).
A Grammar-informed Corpus-based Sentence Database for Linguistic and Computational Studies
We adopt the corpus-informed approach to example sentence selections for the construction of a reference grammar.
