Dan Goldwasser

Orcid: 0000-0001-9326-8601

According to our database1, Dan Goldwasser authored at least 99 papers between 2006 and 2024.

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Bibliography

2024
Post-hoc Study of Climate Microtargeting on Social Media Ads with LLMs: Thematic Insights and Fairness Evaluation.
CoRR, 2024

"Hiding in Plain Sight": Designing Synthetic Dialog Generation for Uncovering Socially Situated Norms.
CoRR, 2024

Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategy.
CoRR, 2024

Uncovering Latent Themes of Messaging on Social Media by Integrating LLMs: A Case Study on Climate Campaigns.
CoRR, 2024

Analysis of State-Level Legislative Process in Enhanced Linguistic and Nationwide Network Contexts.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

An Interactive Framework for Profiling News Media Sources.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

"We Demand Justice!": Towards Social Context Grounding of Political Texts.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Using RL to Identify Divisive Perspectives Improves LLMs Abilities to Identify Communities on Social Media.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023
"We Demand Justice!": Towards Grounding Political Text in Social Context.
CoRR, 2023

Towards Few-Shot Identification of Morality Frames using In-Context Learning.
CoRR, 2023

Interactively Learning Social Media Representations Improves News Source Factuality Detection.
Proceedings of the Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023, 2023

Weakly Supervised Learning for Analyzing Political Campaigns on Facebook.
Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

"A Tale of Two Movements': Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Using LLM for Improving Key Event Discovery: Temporal-Guided News Stream Clustering with Event Summaries.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Automated Attack Synthesis by Extracting Finite State Machines from Protocol Specification Documents.
Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

A Holistic Framework for Analyzing the COVID-19 Vaccine Debate.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Twitter User Representation Using Weakly Supervised Graph Embedding.
Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

Hands-On Interactive Neuro-Symbolic NLP with DRaiL.
Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Towards Explaining Subjective Ground of Individuals on Social Media.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervision.
Proceedings of the IEEE International Conference on Big Data, 2022

Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Analyzing Large Collections of Open-Ended Feedback From MOOC Learners Using LDA Topic Modeling and Qualitative Analysis.
IEEE Trans. Learn. Technol., 2021

Modeling Content and Context with Deep Relational Learning.
Trans. Assoc. Comput. Linguistics, 2021

Modeling Human Mental States with an Entity-based Narrative Graph.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Analysis of Twitter Users' Lifestyle Choices using Joint Embedding Model.
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021

Identifying Morality Frames in Political Tweets using Relational Learning.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Understanding Politics via Contextualized Discourse Processing.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Randomized Deep Structured Prediction for Discourse-Level Processing.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Using Social and Linguistic Information to Adapt Pretrained Representations for Political Perspective Identification.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory.
Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media, 2021

2020
Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness.
IEEE Trans. Vis. Comput. Graph., 2020

Interpretable Engagement Models for MOOCs Using Hinge-Loss Markov Random Fields.
IEEE Trans. Learn. Technol., 2020

Do You Do Yoga? Understanding Twitter Users' Types and Motivations using Social and Textual Information.
CoRR, 2020

"where is this relationship going?": Understanding Relationship Trajectories in Narrative Text.
Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics, 2020

Identifying Collaborative Conversations using Latent Discourse Behaviors.
Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, 2020

Semi-supervised Parsing with a Variational Autoencoding Parser.
Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies, 2020

Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Weakly-Supervised Modeling of Contextualized Event Embedding for Discourse Relations.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Semi-supervised Autoencoding Projective Dependency Parsing.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Predicting Stance Change Using Modular Architectures.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Cross-Lingual Document Retrieval with Smooth Learning.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Does Yoga Make You Happy? Analyzing Twitter User Happiness using Textual and Temporal Information.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Understanding the Language of Political Agreement and Disagreement in Legislative Texts.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
An Anomaly Contribution Explainer for Cyber-Security Applications.
CoRR, 2019

Using Natural Language Relations between Answer Choices for Machine Comprehension.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Improving Natural Language Interaction with Robots Using Advice.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

ACE - An Anomaly Contribution Explainer for Cyber-Security Applications.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Sentiment Tagging with Partial Labels using Modular Architectures.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Multi-Relational Script Learning for Discourse Relations.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

TransConv: Relationship Embedding in Social Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Leveraging Textual Specifications for Grammar-Based Fuzzing of Network Protocols.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Learning from the Ones that Got Away: Detecting New Forms of Phishing Attacks.
IEEE Trans. Dependable Secur. Comput., 2018

Understanding Learners' Opinion about Participation Certificates in Online Courses using Topic Modeling.
Proceedings of the 11th International Conference on Educational Data Mining, 2018

Structured Representation Learning for Online Debate Stance Prediction.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Classification of Moral Foundations in Microblog Political Discourse.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

FEEL: Featured Event Embedding Learning.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
PurdueNLP at SemEval-2017 Task 1: Predicting Semantic Textual Similarity with Paraphrase and Event Embeddings.
Proceedings of the 11th International Workshop on Semantic Evaluation, 2017

Modeling of Political Discourse Framing on Twitter.
Proceedings of the Eleventh International Conference on Web and Social Media, 2017

Semi-supervised Structured Prediction with Neural CRF Autoencoder.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

TATHYA: A Multi-Classifier System for Detecting Check-Worthy Statements in Political Debates.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Leveraging Behavioral and Social Information for Weakly Supervised Collective Classification of Political Discourse on Twitter.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

Ideological Phrase Indicators for Classification of Political Discourse Framing on Twitter.
Proceedings of the Second Workshop on NLP and Computational Social Science, 2017

2016
Understanding Satirical Articles Using Common-Sense.
Trans. Assoc. Comput. Linguistics, 2016

Better Together: Combining Language and Social Interactions into a Shared Representation.
Proceedings of TextGraphs@NAACL-HLT 2016: the 10th Workshop on Graph-based Methods for Natural Language Processing, 2016

Introducing DRAIL - a Step Towards Declarative Deep Relational Learning.
Proceedings of the Workshop on Structured Prediction for NLP@EMNLP 2016, 2016

Adapting Event Embedding for Implicit Discourse Relation Recognition.
Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, 2016

"All I know about politics is what I read in Twitter": Weakly Supervised Models for Extracting Politicians' Stances From Twitter.
Proceedings of the COLING 2016, 2016

Identifying Stance by Analyzing Political Discourse on Twitter.
Proceedings of the First Workshop on NLP and Computational Social Science, 2016

Ask, and Shall You Receive? Understanding Desire Fulfillment in Natural Language Text.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2014
Learning from natural instructions.
Mach. Learn., 2014

Visual analytics of MOOCs at maryland.
Proceedings of the First (2014) ACM Conference on Learning @ Scale, 2014

Uncovering hidden engagement patterns for predicting learner performance in MOOCs.
Proceedings of the First (2014) ACM Conference on Learning @ Scale, 2014

"I Object!" Modeling Latent Pragmatic Effects in Courtroom Dialogues.
Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, 2014

Understanding MOOC Discussion Forums using Seeded LDA.
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications, 2014

Predicting Instructor's Intervention in MOOC forums.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

Learning Latent Engagement Patterns of Students in Online Courses.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Leveraging Domain-Independent Information in Semantic Parsing.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, 2013

2012
Learning from natural instructions
PhD thesis, 2012

Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2012

2011
The Study of Resource Allocation among Software Development Phases: An Economics-Based Approach.
Adv. Softw. Eng., 2011

Structured prediction with indirect supervision.
Proceedings of the 2011 Symposium on Machine Learning in Speech and Language Processing, 2011

Confidence Driven Unsupervised Semantic Parsing.
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 2011

2010
Discriminative Learning over Constrained Latent Representations.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2010

Structured Output Learning with Indirect Supervision.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Driving Semantic Parsing from the World's Response.
Proceedings of the Fourteenth Conference on Computational Natural Language Learning, 2010

2009
Relation Alignment for Textual Entailment Recognition.
Proceedings of the Second Text Analysis Conference, 2009

Unsupervised Constraint Driven Learning For Transliteration Discovery.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, May 31, 2009

Reading to Learn: Constructing Features from Semantic Abstracts.
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009

2008
A Theory-Based Decision Heuristic for DPLL(T).
Proceedings of the Formal Methods in Computer-Aided Design, 2008

Transliteration as Constrained Optimization.
Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, 2008

Active Sample Selection for Named Entity Transliteration.
Proceedings of the ACL 2008, 2008

2007
Analyzing Museum Visitors' Behavior Patterns.
Proceedings of the User Modeling 2007, 11th International Conference, 2007

2006
Identifying Inter-Domain Similarities Through Content-Based Analysis of Hierarchical Web-Directories.
Proceedings of the ECAI 2006, 17th European Conference on Artificial Intelligence, August 29, 2006


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