Swapna Somasundaran


2021

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Training and Domain Adaptation for Supervised Text Segmentation
Goran Glavaš | Ananya Ganesh | Swapna Somasundaran
Proceedings of the 16th Workshop on Innovative Use of NLP for Building Educational Applications

Unlike traditional unsupervised text segmentation methods, recent supervised segmentation models rely on Wikipedia as the source of large-scale segmentation supervision. These models have, however, predominantly been evaluated on the in-domain (Wikipedia-based) test sets, preventing conclusions about their general segmentation efficacy. In this work, we focus on the domain transfer performance of supervised neural text segmentation in the educational domain. To this end, we first introduce K12Seg, a new dataset for evaluation of supervised segmentation, created from educational reading material for grade-1 to college-level students. We then benchmark a hierarchical text segmentation model (HITS), based on RoBERTa, in both in-domain and domain-transfer segmentation experiments. While HITS produces state-of-the-art in-domain performance (on three Wikipedia-based test sets), we show that, subject to the standard full-blown fine-tuning, it is susceptible to domain overfitting. We identify adapter-based fine-tuning as a remedy that substantially improves transfer performance.

2020

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Emotion Arcs of Student Narratives
Swapna Somasundaran | Xianyang Chen | Michael Flor
Proceedings of the First Joint Workshop on Narrative Understanding, Storylines, and Events

This paper studies emotion arcs in student narratives. We construct emotion arcs based on event affect and implied sentiments, which correspond to plot elements in the story. We show that student narratives can show elements of plot structure in their emotion arcs and that properties of these arcs can be useful indicators of narrative quality. We build a system and perform analysis to show that our arc-based features are complementary to previously studied sentiment features in this area.

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Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs)
Dmitry Ustalov | Swapna Somasundaran | Alexander Panchenko | Fragkiskos D. Malliaros | Ioana Hulpuș | Peter Jansen | Abhik Jana
Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs)

2019

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Lexical concreteness in narrative
Michael Flor | Swapna Somasundaran
Proceedings of the Second Workshop on Storytelling

This study explores the relation between lexical concreteness and narrative text quality. We present a methodology to quantitatively measure lexical concreteness of a text. We apply it to a corpus of student stories, scored according to writing evaluation rubrics. Lexical concreteness is weakly-to-moderately related to story quality, depending on story-type. The relation is mostly borne by adjectives and nouns, but also found for adverbs and verbs.

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Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
Dmitry Ustalov | Swapna Somasundaran | Peter Jansen | Goran Glavaš | Martin Riedl | Mihai Surdeanu | Michalis Vazirgiannis
Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)

2018

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Towards Evaluating Narrative Quality In Student Writing
Swapna Somasundaran | Michael Flor | Martin Chodorow | Hillary Molloy | Binod Gyawali | Laura McCulla
Transactions of the Association for Computational Linguistics, Volume 6

This work lays the foundation for automated assessments of narrative quality in student writing. We first manually score essays for narrative-relevant traits and sub-traits, and measure inter-annotator agreement. We then explore linguistic features that are indicative of good narrative writing and use them to build an automated scoring system. Experiments show that our features are more effective in scoring specific aspects of narrative quality than a state-of-the-art feature set.

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Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12)
Goran Glavaš | Swapna Somasundaran | Martin Riedl | Eduard Hovy
Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12)

2017

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Sentiment Analysis and Lexical Cohesion for the Story Cloze Task
Michael Flor | Swapna Somasundaran
Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics

We present two NLP components for the Story Cloze Task – dictionary-based sentiment analysis and lexical cohesion. While previous research found no contribution from sentiment analysis to the accuracy on this task, we demonstrate that sentiment is an important aspect. We describe a new approach, using a rule that estimates sentiment congruence in a story. Our sentiment-based system achieves strong results on this task. Our lexical cohesion system achieves accuracy comparable to previously published baseline results. A combination of the two systems achieves better accuracy than published baselines. We argue that sentiment analysis should be considered an integral part of narrative comprehension.

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Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing
Martin Riedl | Swapna Somasundaran | Goran Glavaš | Eduard Hovy
Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing

2016

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Evaluating Argumentative and Narrative Essays using Graphs
Swapna Somasundaran | Brian Riordan | Binod Gyawali | Su-Youn Yoon
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

This work investigates whether the development of ideas in writing can be captured by graph properties derived from the text. Focusing on student essays, we represent the essay as a graph, and encode a variety of graph properties including PageRank as features for modeling essay scores related to quality of development. We demonstrate that our approach improves on a state-of-the-art system on the task of holistic scoring of persuasive essays and on the task of scoring narrative essays along the development dimension.

2015

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Automated Scoring of Picture-based Story Narration
Swapna Somasundaran | Chong Min Lee | Martin Chodorow | Xinhao Wang
Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications

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Scoring Persuasive Essays Using Opinions and their Targets
Noura Farra | Swapna Somasundaran | Jill Burstein
Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications

2014

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Content Importance Models for Scoring Writing From Sources
Beata Beigman Klebanov | Nitin Madnani | Jill Burstein | Swapna Somasundaran
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Automated Measures of Specific Vocabulary Knowledge from Constructed Responses (‘Use These Words to Write a Sentence Based on this Picture’)
Swapna Somasundaran | Martin Chodorow
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications

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Finding your “Inner-Annotator”: An Experiment in Annotator Independence for Rating Discourse Coherence Quality in Essays
Jill Burstein | Swapna Somasundaran | Martin Chodorow
Proceedings of LAW VIII - The 8th Linguistic Annotation Workshop

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Lexical Chaining for Measuring Discourse Coherence Quality in Test-taker Essays
Swapna Somasundaran | Jill Burstein | Martin Chodorow
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

2011

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A Combination of Topic Models with Max-margin Learning for Relation Detection
Dingcheng Li | Swapna Somasundaran | Amit Chakraborty
Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing

2010

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Recognizing Stances in Ideological On-Line Debates
Swapna Somasundaran | Janyce Wiebe
Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text

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Proceedings of TextGraphs-5 - 2010 Workshop on Graph-based Methods for Natural Language Processing
Carmen Banea | Alessandro Moschitti | Swapna Somasundaran | Fabio Massimo Zanzotto
Proceedings of TextGraphs-5 - 2010 Workshop on Graph-based Methods for Natural Language Processing

2009

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Supervised and Unsupervised Methods in Employing Discourse Relations for Improving Opinion Polarity Classification
Swapna Somasundaran | Galileo Namata | Janyce Wiebe | Lise Getoor
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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Recognizing Stances in Online Debates
Swapna Somasundaran | Janyce Wiebe
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

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Opinion Graphs for Polarity and Discourse Classification
Swapna Somasundaran | Galileo Namata | Lise Getoor | Janyce Wiebe
Proceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing (TextGraphs-4)

2008

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Finding the Sources and Targets of Subjective Expressions
Josef Ruppenhofer | Swapna Somasundaran | Janyce Wiebe
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

As many popular text genres such as blogs or news contain opinions by multiple sources and about multiple targets, finding the sources and targets of subjective expressions becomes an important sub-task for automatic opinion analysis systems. We argue that while automatic semantic role labeling systems (ASRL) have an important contribution to make, they cannot solve the problem for all cases. Based on the experience of manually annotating opinions, sources, and targets in various genres, we present linguistic phenomena that require knowledge beyond that of ASRL systems. In particular, we address issues relating to the attribution of opinions to sources; sources and targets that are realized as zero-forms; and inferred opinions. We also discuss in some depth that for arguing attitudes we need to be able to recover propositions and not only argued-about entities. A recurrent theme of the discussion is that close attention to specific discourse contexts is needed to identify sources and targets correctly.

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Discourse Level Opinion Interpretation
Swapna Somasundaran | Janyce Wiebe | Josef Ruppenhofer
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

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Discourse Level Opinion Relations: An Annotation Study
Swapna Somasundaran | Josef Ruppenhofer | Janyce Wiebe
Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue

2007

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Detecting Arguing and Sentiment in Meetings
Swapna Somasundaran | Josef Ruppenhofer | Janyce Wiebe
Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue

2006

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Manual Annotation of Opinion Categories in Meetings
Swapna Somasundaran | Janyce Wiebe | Paul Hoffmann | Diane Litman
Proceedings of the Workshop on Frontiers in Linguistically Annotated Corpora 2006

2005

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OpinionFinder: A System for Subjectivity Analysis
Theresa Wilson | Paul Hoffmann | Swapna Somasundaran | Jason Kessler | Janyce Wiebe | Yejin Choi | Claire Cardie | Ellen Riloff | Siddharth Patwardhan
Proceedings of HLT/EMNLP 2005 Interactive Demonstrations