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Found 110 papers, 15 papers with code
Developing Conversational Data and Detection of Conversational Humor in Telugu
(a) develop a conversational (humorous and non-humorous) dataset in Telugu.
Towards Toxic Positivity Detection
Over the past few years, there has been a growing concern around toxic positivity on social media which is a phenomenon where positivity is used to minimize one’s emotional experience.
Sammaan@LT-EDI-ACL2022: Ensembled Transformers Against Homophobia and Transphobia
Hateful and offensive content on social media platforms can have negative effects on users and can make online communities more hostile towards certain people and hamper equality, diversity and inclusion.
A Novel Annotation Schema for Conversational Humor: Capturing the Cultural Nuances in Kanyasulkam
Humor research is a multifaceted field that has led to a better understanding of humor’s psychological effects and the development of different theories of humor.
TeluguNER: Leveraging Multi-Domain Named Entity Recognition with Deep Transformers
Our contributions in this paper include (i) Two annotated NER datasets for the Telugu language in multiple domains: Newswire Dataset (ND) and Medical Dataset (MD), and we combined ND and MD to form Combined Dataset (CD) (ii) Comparison of the finetuned Telugu pretrained transformer models (BERT-Te, RoBERTa-Te, and ELECTRA-Te) with other baseline models (CRF, LSTM-CRF, and BiLSTM-CRF) (iii) Further investigation of the performance of Telugu pretrained transformer models against the multilingual models mBERT, XLM-R, and IndicBERT.
Graph Convolutional Networks with Multi-headed Attention for Code-Mixed Sentiment Analysis
In this paper, we propose the graph convolutional networks (GCN) for sentiment analysis on code-mixed text.
Towards Detecting Political Bias in Hindi News Articles
Political propaganda in recent times has been amplified by media news portals through biased reporting, creating untruthful narratives on serious issues causing misinformed public opinions with interests of siding and helping a particular political party.
Towards Sentiment Analysis of Tobacco Products’ Usage in Social Media
We release SentiSmoke-Twitter and SentiSmoke-Reddit datasets, along with a comprehensive annotation schema for identifying tobacco products’ sentiment.
Sentiment Analysis in Code-Mixed Telugu-English Text with Unsupervised Data Normalization
In a multilingual society, people communicate in more than one language, leading to Code-Mixed data.
Corpus Creation and Language Identification in Low-Resource Code-Mixed Telugu-English Text
In the current era of machine learning, a common problem to the above-mentioned tasks is the availability of Learning data to train models.
Towards Quantifying Magnitude of Political Bias in News Articles Using a Novel Annotation Schema
We create a ranking of these techniques based on their contribution to bias.
A Pre-trained Transformer and CNN Model with Joint Language ID and Part-of-Speech Tagging for Code-Mixed Social-Media Text
We train a joint learning method by combining POS tagging and LI models on code-mixed social media text obtained from the ICON shared task.
TEASER: Towards Efficient Aspect-based SEntiment Analysis and Recognition
Prior works formulate this as a sequence tagging problem or solve this task using a span-based extract-then-classify framework where first all the opinion targets are extracted from the sentence, and then with the help of span representations, the targets are classified as positive, negative, or neutral.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Efficient Multilingual Text Classification for Indian Languages
Can a classification model trained on one Indian language be reused for other Indian languages?
Automatic Learning Assistant in Telugu
We built our learning assistant for Telugu language to help with teaching in the mother tongue, which is the most efficient way of learning.
Multichannel LSTM-CNN for Telugu Text Classification
With the instantaneous growth of text information, retrieving domain-oriented information from the text data has a broad range of applications in Information Retrieval and Natural language Processing.
Leveraging Multilingual Resources for Language Invariant Sentiment Analysis
Sentiment analysis is a widely researched NLP problem with state-of-the-art solutions capable of attaining human-like accuracies for various languages.
OFFLangOne@DravidianLangTech-EACL2021: Transformers with the Class Balanced Loss for Offensive Language Identification in Dravidian Code-Mixed text.
In a multilingual society, where code-mixing is a norm, the hate content would be delivered in a code-mixed form in social media, which makes the offensive content identification, further challenging.
EDIOne@LT-EDI-EACL2021: Pre-trained Transformers with Convolutional Neural Networks for Hope Speech Detection.
Hope is an essential aspect of mental health stability and recovery in every individual in this fast-changing world.
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse
Online abuse and offensive language on social media have become widespread problems in today’s digital age.
LastResort at SemEval-2022 Task 5: Towards Misogyny Identification using Visual Linguistic Model Ensembles And Task-Specific Pretraining
In current times, memes have become one of the most popular mediums to share jokes and information with the masses over the internet.
LastResort at SemEval-2022 Task 4: Towards Patronizing and Condescending Language Detection using Pre-trained Transformer Based Models Ensembles
For the second sub-task, given a paragraph, we have to find which PCL categories express the condescension.
DepressionOne@LT-EDI-ACL2022: Using Machine Learning with SMOTE and Random UnderSampling to Detect Signs of Depression on Social Media Text.
Later, we used machine learning methods to train and detect the signs of depression.
Gated Convolutional Sequence to Sequence Based Learning for English-Hingilsh Code-Switched Machine Translation.
Code-Switching is the embedding of linguistic units or phrases from two or more languages in a single sentence.
Political Discourse Analysis: A Case Study of Code Mixing and Code Switching in Political Speeches
Political discourse is one of the most interesting data to study power relations in the framework of Critical Discourse Analysis.
Question and Answer pair generation for Telugu short stories
Question Answer pair generation is a task that has been worked upon by multiple researchers in many languages.
SUKHAN: Corpus of Hindi Shayaris annotated with Sentiment Polarity Information
To the best of our knowledge, this is the first corpus of Hindi shayaris annotated with sentiment polarity information.
Samajh-Boojh: A Reading Comprehension system in Hindi
To the best of our knowledge, the proposed design is first of its kind which accounts for entire process of comprehending the passage and then answering the questions associated with the passage.
Hopeful Men@LT-EDI-EACL2021: Hope Speech Detection Using Indic Transliteration and Transformers
This paper aims to describe the approach we used to detect hope speech in the HopeEDI dataset.
Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model
The rapid rise of online social networks like YouTube, Facebook, Twitter allows people to express their views more widely online.
Zero-Shot Multi-task Hallucination Detection
In recent studies, the extensive utilization of large language models has underscored the importance of robust evaluation methodologies for assessing text generation quality and relevance to specific tasks.
SemEval-2024 Task 8: Weighted Layer Averaging RoBERTa for Black-Box Machine-Generated Text Detection
This document contains the details of the authors' submission to the proceedings of SemEval 2024's Task 8: Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection Subtask A (monolingual) and B.
GAE-ISumm: Unsupervised Graph-Based Summarization of Indian Languages
Further, we experiment with the most publicly available Indian language summarization datasets to investigate the effectiveness of GAE-ISumm on other Indian languages.
Using Selective Masking as a Bridge between Pre-training and Fine-tuning
Following this standard supervised fine-tuning is done for different downstream tasks.
CMNEROne at SemEval-2022 Task 11: Code-Mixed Named Entity Recognition by leveraging multilingual data
Our work consists of Named Entity Recognition (NER) on the code-mixed dataset by leveraging the multilingual data.
cViL: Cross-Lingual Training of Vision-Language Models using Knowledge Distillation
We propose a pipeline that utilizes English-only vision-language models to train a monolingual model for a target language.
Detection of Propaganda Techniques in Visuo-Lingual Metaphor in Memes
The exponential rise of social media networks has allowed the production, distribution, and consumption of data at a phenomenal rate.
Multi-Task Text Classification using Graph Convolutional Networks for Large-Scale Low Resource Language
Graph Convolutional Networks (GCN) have achieved state-of-art results on single text classification tasks like sentiment analysis, emotion detection, etc.
On the Importance of Karaka Framework in Multi-modal Grounding
Computational Paninian Grammar model helps in decoding a natural language expression as a series of modifier-modified relations and therefore facilitates in identifying dependency relations closer to language (context) semantics compared to the usual Stanford dependency relations.
How do different factors Impact the Inter-language Similarity? A Case Study on Indian languages
India is one of the most linguistically diverse nations of the world and is culturally very rich.
IIITH at SemEval-2021 Task 7: Leveraging transformer-based humourous and offensive text detection architectures using lexical and hurtlex features and task adaptive pretraining
This paper describes our approach (IIITH) for SemEval-2021 Task 5: HaHackathon: Detecting and Rating Humor and Offense.
Volta at SemEval-2021 Task 6: Towards Detecting Persuasive Texts and Images using Textual and Multimodal Ensemble
Memes are one of the most popular types of content used to spread information online.
ViTA: Visual-Linguistic Translation by Aligning Object Tags
Multimodal Machine Translation (MMT) enriches the source text with visual information for translation.
Ranked #1 on
Multimodal Machine Translation
on Hindi Visual Genome (Test Set)
(using extra training data)
Detection of Fake Users in SMPs Using NLP and Graph Embeddings
Social Media Platforms (SMPs) like Facebook, Twitter, Instagram etc.
Towards Conversational Humor Analysis and Design
Well-defined jokes can be divided neatly into a setup and a punchline.
Hopeful_Men@LT-EDI-EACL2021: Hope Speech Detection Using Indic Transliteration and Transformers
Our solution got a weighted F1 score of 0. 93, 0. 75 and 0. 49 for English, Malayalam and Tamil respectively.
Multichannel LSTM-CNN for Telugu Technical Domain Identification
With the instantaneous growth of text information, retrieving domain-oriented information from the text data has a broad range of applications in Information Retrieval and Natural language Processing.
Analyzing Curriculum Learning for Sentiment Analysis along Task Difficulty, Pacing and Visualization Axes
Our axes of analysis include Task difficulty on CL, comparing CL pacing techniques, and qualitative analysis by visualizing the movement of attention scores in the model as curriculum phases progress.
Multilingual Pre-Trained Transformers and Convolutional NN Classification Models for Technical Domain Identification
In this paper, we present a transfer learning system to perform technical domain identification on multilingual text data.
Does a Hybrid Neural Network based Feature Selection Model Improve Text Classification?
These features increase the complexity of the classification algorithm.
CMSAOne@Dravidian-CodeMix-FIRE2020: A Meta Embedding and Transformer model for Code-Mixed Sentiment Analysis on Social Media Text
We used the proposed method for the Task: "Sentiment Analysis for Dravidian Languages in Code-Mixed Text", and it achieved an F1 score of $0. 58$ and $0. 66$ for the given Dravidian code mixed data sets.
HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection
Hateful and Toxic content has become a significant concern in today's world due to an exponential rise in social media.
Transformer based Automatic COVID-19 Fake News Detection System
For our analysis in this paper, we report a methodology to analyze the reliability of information shared on social media pertaining to the COVID-19 pandemic.
gundapusunil at SemEval-2020 Task 9: Syntactic Semantic LSTM Architecture for SENTIment Analysis of Code-MIXed Data
Our system first generates two types of embeddings for the social media text.
gundapusunil at SemEval-2020 Task 8: Multimodal Memotion Analysis
Recent technological advancements in the Internet and Social media usage have resulted in the evolution of faster and efficient platforms of communication.
Word Level Language Identification in English Telugu Code Mixed Data
In a multilingual or sociolingual configuration Intra-sentential Code Switching (ICS) or Code Mixing (CM) is frequently observed nowadays.
Enhancing Bias Detection in Political News Using Pragmatic Presupposition
Usage of presuppositions in social media and news discourse can be a powerful way to influence the readers as they usually tend to not examine the truth value of the hidden or indirectly expressed information.
Detecting Sarcasm in Conversation Context Using Transformer-Based Models
Sarcasm detection, regarded as one of the sub-problems of sentiment analysis, is a very typical task because the introduction of sarcastic words can flip the sentiment of the sentence itself.
BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text
There is a growing interest in understanding how humans initiate and hold conversations.
Ranked #1 on
Text Classification
on AffCon 2020 Emotion Detection
A SentiWordNet Strategy for Curriculum Learning in Sentiment Analysis
In this paper, we apply the ideas of curriculum learning, driven by SentiWordNet in a sentiment analysis setting.
Manovaad: A Novel Approach to Event Oriented Corpus Creation Capturing Subjectivity and Focus
In today{'}s era of globalisation, the increased outreach for every event across the world has been leading to conflicting opinions, arguments and disagreements, often reflected in print media and online social platforms.
Dataset Creation and Evaluation of Aspect Based Sentiment Analysis in Telugu, a Low Resource Language
Aspect Based Sentiment Analysis (ABSA) is an area of sentiment analysis which deals with sentiment at a finer level.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
Annotated Corpus for Sentiment Analysis in Odia Language
Given the lack of an annotated corpus of non-traditional Odia literature which serves as the standard when it comes sentiment analysis, we have created an annotated corpus of Odia sentences and made it publicly available to promote research in the field.
SentiInc: Incorporating Sentiment Information into Sentiment Transfer Without Parallel Data
We address this issue by providing a simple framework for encoding sentiment-specific information in the target sentence while preserving the content information.
Ranked #1 on
Text Style Transfer
on Yelp Review Dataset (Large)
Towards Detection of Subjective Bias using Contextualized Word Embeddings
Subjective bias detection is critical for applications like propaganda detection, content recommendation, sentiment analysis, and bias neutralization.
Ranked #1 on
Bias Detection
on Wiki Neutrality Corpus
Conversational implicatures in English dialogue: Annotated dataset
But in human-computer interactions, the machine fails to understand the implicated meaning unless it is trained with a dataset containing the implicated meaning of an utterance along with the utterance and the context in which it is uttered.
Anaphora Resolution in Dialogue Systems for South Asian Languages
Anaphora resolution is a challenging task which has been the interest of NLP researchers for a long time.
Samvaadhana: A Telugu Dialogue System in Hospital Domain
In this paper, a dialogue system for Hospital domain in Telugu, which is a resource-poor Dravidian language, has been built.
Towards Computing Inferences from English News Headlines
Newspapers are a popular form of written discourse, read by many people, thanks to the novelty of the information provided by the news content in it.
SmokEng: Towards Fine-grained Classification of Tobacco-related Social Media Text
Contemporary datasets on tobacco consumption focus on one of two topics, either public health mentions and disease surveillance, or sentiment analysis on topical tobacco products and services.
Detecting Political Bias in News Articles Using Headline Attention
Language is a powerful tool which can be used to state the facts as well as express our views and perceptions.
Hindi Question Generation Using Dependency Structures
We present a rule-based system for question generation in Hindi by formalizing question transformation methods based on karaka-dependency theory.
Deep Learning Techniques for Humor Detection in Hindi-English Code-Mixed Tweets
We propose bilingual word embeddings based on word2vec and fastText models (CBOW and Skip-gram) to address the problem of Humor detection in Hindi-English code-mixed tweets in combination with deep learning architectures.
Stance Detection in Code-Mixed Hindi-English Social Media Data using Multi-Task Learning
We apply our approach on Hindi-English code-mixed corpus against the target entity - {``}Demonetisation.
Affect in Tweets Using Experts Model
We compared the results of our Experts Model with both baseline results and top five performers of SemEval-2018 Task-1, Affect in Tweets (AIT).
Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis
With this as basis, we aim to analyze the importance of sense-annotations obtained from OntoSenseNet in performing the task of sentiment analysis.
Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu)
In this paper, we discuss the enrichment of a manually developed resource of Telugu lexicon, OntoSenseNet.
BCSAT : A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations
The presented work aims at generating a systematically annotated corpus that can support the enhancement of sentiment analysis tasks in Telugu using word-level sentiment annotations.
Automatic Spelling Correction for Resource-Scarce Languages using Deep Learning
Spelling correction is a well-known task in Natural Language Processing (NLP).
Towards Automation of Sense-type Identification of Verbs in OntoSenseNet
In this paper, we discuss the enrichment of a manually developed resource, OntoSenseNet for Telugu.
Exploring Chunk Based Templates for Generating a subset of English Text
Natural Language Generation (NLG) is a research task which addresses the automatic generation of natural language text representative of an input non-linguistic collection of knowledge.
Automatic Target Recovery for Hindi-English Code Mixed Puns
In particular, we consider code-mixed puns which have become increasingly mainstream on social media, in informal conversations and advertisements and aim to build a system which can automatically identify the pun location and recover the target of such puns.
Addition of Code Mixed Features to Enhance the Sentiment Prediction of Song Lyrics
The song lyric is a rich source of datasets containing words that are helpful in analysis and classification of sentiments generated from it.
"How to rate a video game?" - A prediction system for video games based on multimodal information
A straightforward approach would be to predict the scores of video games based on other information related to the game.
Context and Humor: Understanding Amul advertisements of India
Contextual knowledge is the most important element in understanding language.
ACTSA: Annotated Corpus for Telugu Sentiment Analysis
The corpus, named ACTSA (Annotated Corpus for Telugu Sentiment Analysis) has a collection of Telugu sentences taken from different sources which were then pre-processed and manually annotated by native Telugu speakers using our annotation guidelines.
Building a SentiWordNet for Odia
One solution is to use available resources in English and translate the final source lexicon to target lexicon via machine translation.
When does a compliment become sexist? Analysis and classification of ambivalent sexism using twitter data
Our work helps analyze and understand the much prevalent ambivalent sexism in social media.
Experiments in Linear Template Combination using Genetic Algorithms
We posit the construction of a sentence as a highly restricted sequence of such templates.
Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text
In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed.
