Search Results for author: Firoj Alam

Found 43 papers, 17 papers with code

COVID-19 in Bulgarian Social Media: Factuality, Harmfulness, Propaganda, and Framing

1 code implementation RANLP 2021 Preslav Nakov, Firoj Alam, Shaden Shaar, Giovanni Da San Martino, Yifan Zhang

With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic.

Punctuation Restoration using Transformer Models for High-and Low-Resource Languages

1 code implementation EMNLP (WNUT) 2020 Tanvirul Alam, Akib Khan, Firoj Alam

In this work, we explore different transformer based models and propose an augmentation strategy for this task, focusing on high-resource (English) and low-resource (Bangla) languages.

Automatic Speech Recognition Punctuation Restoration

Analyzing Encoded Concepts in Transformer Language Models

1 code implementation27 Jun 2022 Hassan Sajjad, Nadir Durrani, Fahim Dalvi, Firoj Alam, Abdul Rafae Khan, Jia Xu

We propose a novel framework ConceptX, to analyze how latent concepts are encoded in representations learned within pre-trained language models.

Discovering Latent Concepts Learned in BERT

no code implementations ICLR 2022 Fahim Dalvi, Abdul Rafae Khan, Firoj Alam, Nadir Durrani, Jia Xu, Hassan Sajjad

We address this limitation by discovering and analyzing latent concepts learned in neural network models in an unsupervised fashion and provide interpretations from the model's perspective.


Detecting the Role of an Entity in Harmful Memes: Techniques and Their Limitations

1 code implementation CONSTRAINT (ACL) 2022 Rabindra Nath Nandi, Firoj Alam, Preslav Nakov

The content that is posted and shared online can be textual, visual, or a combination of both, e. g., in a meme.

TeamX@DravidianLangTech-ACL2022: A Comparative Analysis for Troll-Based Meme Classification

no code implementations DravidianLangTech (ACL) 2022 Rabindra Nath Nandi, Firoj Alam, Preslav Nakov

The spread of fake news, propaganda, misinformation, disinformation, and harmful content online raised concerns among social media platforms, government agencies, policymakers, and society as a whole.

Meme Classification Misinformation

Detecting and Understanding Harmful Memes: A Survey

1 code implementation9 May 2022 Shivam Sharma, Firoj Alam, Md. Shad Akhtar, Dimitar Dimitrov, Giovanni Da San Martino, Hamed Firooz, Alon Halevy, Fabrizio Silvestri, Preslav Nakov, Tanmoy Chakraborty

One interesting finding is that many types of harmful memes are not really studied, e. g., such featuring self-harm and extremism, partly due to the lack of suitable datasets.

QCRI's COVID-19 Disinformation Detector: A System to Fight the COVID-19 Infodemic in Social Media

no code implementations8 Mar 2022 Preslav Nakov, Firoj Alam, Yifan Zhang, Animesh Prakash, Fahim Dalvi

Fighting the ongoing COVID-19 infodemic has been declared as one of the most important focus areas by the World Health Organization since the onset of the COVID-19 pandemic.

ArabGend: Gender Analysis and Inference on Arabic Twitter

no code implementations1 Mar 2022 Hamdy Mubarak, Shammur Absar Chowdhury, Firoj Alam

Gender analysis of Twitter can reveal important socio-cultural differences between male and female users.

A Second Pandemic? Analysis of Fake News About COVID-19 Vaccines in Qatar

no code implementations RANLP 2021 Preslav Nakov, Firoj Alam, Shaden Shaar, Giovanni Da San Martino, Yifan Zhang

While COVID-19 vaccines are finally becoming widely available, a second pandemic that revolves around the circulation of anti-vaxxer fake news may hinder efforts to recover from the first one.

Detecting Propaganda Techniques in Memes

1 code implementation ACL 2021 Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, Firoj Alam, Fabrizio Silvestri, Hamed Firooz, Preslav Nakov, Giovanni Da San Martino

We further create and release a new corpus of 950 memes, carefully annotated with 22 propaganda techniques, which can appear in the text, in the image, or in both.

A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models

1 code implementation8 Jul 2021 Firoj Alam, Arid Hasan, Tanvirul Alam, Akib Khan, Janntatul Tajrin, Naira Khan, Shammur Absar Chowdhury

In this study, we first provide a review of Bangla NLP tasks, resources, and tools available to the research community; we benchmark datasets collected from various platforms for nine NLP tasks using current state-of-the-art algorithms (i. e., transformer-based models).

Natural Language Processing

SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images

1 code implementation SEMEVAL 2021 Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, Firoj Alam, Fabrizio Silvestri, Hamed Firooz, Preslav Nakov, Giovanni Da San Martino

We describe SemEval-2021 task 6 on Detection of Persuasion Techniques in Texts and Images: the data, the annotation guidelines, the evaluation setup, the results, and the participating systems.

Effect of Post-processing on Contextualized Word Representations

no code implementations15 Apr 2021 Hassan Sajjad, Firoj Alam, Fahim Dalvi, Nadir Durrani

However, post-processing for contextualized embeddings is an under-studied problem.

Word Similarity

Robust Training of Social Media Image Classification Models for Rapid Disaster Response

no code implementations9 Apr 2021 Firoj Alam, Tanvirul Alam, Muhammad Imran, Ferda Ofli

Images shared on social media help crisis managers gain situational awareness and assess incurred damages, among other response tasks.

Data Augmentation Disaster Response +3

HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks

no code implementations7 Apr 2021 Firoj Alam, Umair Qazi, Muhammad Imran, Ferda Ofli

Social networks are widely used for information consumption and dissemination, especially during time-critical events such as natural disasters.

Decision Making

Automated Fact-Checking for Assisting Human Fact-Checkers

no code implementations13 Mar 2021 Preslav Nakov, David Corney, Maram Hasanain, Firoj Alam, Tamer Elsayed, Alberto Barrón-Cedeño, Paolo Papotti, Shaden Shaar, Giovanni Da San Martino

The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism.

Fact Checking

Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset

no code implementations1 Mar 2021 Kashif Ahmad, Firoj Alam, Junaid Qadir, Basheer Qolomany, Imran Khan, Talhat Khan, Muhammad Suleman, Naina Said, Syed Zohaib Hassan, Asma Gul, Ala Al-Fuqaha

In this work, we propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users' reviews.

Sentiment Analysis

Flood Detection via Twitter Streams using Textual and Visual Features

no code implementations30 Nov 2020 Firoj Alam, Zohaib Hassan, Kashif Ahmad, Asma Gul, Michael Reiglar, Nicola Conci, Ala Al-Fuqaha

The paper presents our proposed solutions for the MediaEval 2020 Flood-Related Multimedia Task, which aims to analyze and detect flooding events in multimedia content shared over Twitter.

Sentiment Classification in Bangla Textual Content: A Comparative Study

1 code implementation19 Nov 2020 Md. Arid Hasan, Jannatul Tajrin, Shammur Absar Chowdhury, Firoj Alam

In this study, we explore several publicly available sentiment labeled datasets and designed classifiers using both classical and deep learning algorithms.

Classification General Classification +1

Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response

no code implementations17 Nov 2020 Firoj Alam, Ferda Ofli, Muhammad Imran, Tanvirul Alam, Umair Qazi

In this study, we propose new datasets for disaster type detection, and informativeness classification, and damage severity assessment.

Disaster Response General Classification +3

Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms

1 code implementation15 Jul 2020 Firoj Alam, Fahim Dalvi, Shaden Shaar, Nadir Durrani, Hamdy Mubarak, Alex Nikolov, Giovanni Da San Martino, Ahmed Abdelali, Hassan Sajjad, Kareem Darwish, Preslav Nakov

With the outbreak of the COVID-19 pandemic, people turned to social media to read and to share timely information including statistics, warnings, advice, and inspirational stories.


CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing

no code implementations14 Apr 2020 Firoj Alam, Hassan Sajjad, Muhammad Imran, Ferda Ofli

Time-critical analysis of social media streams is important for humanitarian organizations for planing rapid response during disasters.

General Classification Humanitarian +1

Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence

no code implementations14 Apr 2020 Muhammad Imran, Firoj Alam, Umair Qazi, Steve Peterson, Ferda Ofli

Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings.

Domain Adaptation with Adversarial Training and Graph Embeddings

1 code implementation ACL 2018 Firoj Alam, Shafiq Joty, Muhammad Imran

In such scenarios, a DNN model can leverage labeled and unlabeled data from a related domain, but it has to deal with the shift in data distributions between the source and the target domains.

Domain Adaptation

CrisisMMD: Multimodal Twitter Datasets from Natural Disasters

2 code implementations2 May 2018 Firoj Alam, Ferda Ofli, Muhammad Imran

Despite extensive research that mainly focuses on textual content to extract useful information, limited work has focused on the use of imagery content or the combination of both content types.

Social and Information Networks Computers and Society

Graph Based Semi-supervised Learning with Convolution Neural Networks to Classify Crisis Related Tweets

no code implementations2 May 2018 Firoj Alam, Shafiq Joty, Muhammad Imran

During time-critical situations such as natural disasters, rapid classification of data posted on social networks by affected people is useful for humanitarian organizations to gain situational awareness and to plan response efforts.

General Classification Humanitarian

Annotating and Modeling Empathy in Spoken Conversations

no code implementations13 May 2017 Firoj Alam, Morena Danieli, Giuseppe Riccardi

The automatic classification system was evaluated on call center conversations where it showed significantly better performance than the baseline.

General Classification

Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises

no code implementations9 Apr 2017 Dat Tien Nguyen, Firoj Alam, Ferda Ofli, Muhammad Imran

The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly.


How Interlocutors Coordinate with each other within Emotional Segments?

no code implementations COLING 2016 Firoj Alam, Shammur Absar Chowdhury, Morena Danieli, Giuseppe Riccardi

In this paper, we aim to investigate the coordination of interlocutors behavior in different emotional segments.

Multilevel Annotation of Agreement and Disagreement in Italian News Blogs

no code implementations LREC 2016 Fabio Celli, Giuseppe Riccardi, Firoj Alam

In this paper, we present a corpus of news blog conversations in Italian annotated with gold standard agreement/disagreement relations at message and sentence levels.

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