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- affiliation: University of Stuttgart, Institute for Natural Language Processing, Germany
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2020 – today
- 2024
[c87]Amelie Wührl, Dustin Wright, Roman Klinger, Isabelle Augenstein:
Understanding Fine-grained Distortions in Reports of Scientific Findings. ACL (Findings) 2024: 6175-6191- [c86]Aswathy Velutharambath, Roman Klinger, Amelie Wührl:
Can Factual Statements Be Deceptive? The DeFaBel Corpus of Belief-based Deception. LREC/COLING 2024: 2708-2723 - [c85]Eileen Wemmer
, Sofie Labat, Roman Klinger:
EmoProgress: Cumulated Emotion Progression Analysis in Dreams and Customer Service Dialogues. LREC/COLING 2024: 5660-5677 - [c84]Amelie Wührl, Yarik Menchaca Resendiz, Lara Grimminger, Roman Klinger:
What Makes Medical Claims (Un)Verifiable? Analyzing Entity and Relation Properties for Fact Verification. EACL (1) 2024: 2046-2058 - [c83]Enrica Troiano, Sofie Labat, Marco Stranisci, Rossana Damiano, Viviana Patti, Roman Klinger:
Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing. EMNLP (Findings) 2024: 1634-1658 - [c82]Aswathy Velutharambath, Amelie Wührl, Roman Klinger:
How Entangled is Factuality and Deception in German? EMNLP (Findings) 2024: 9538-9554 - [c81]Christopher Bagdon, Prathamesh Karmalkar, Harsha Gurulingappa, Roman Klinger:
"You are an expert annotator": Automatic Best-Worst-Scaling Annotations for Emotion Intensity Modeling. NAACL-HLT 2024: 7924-7936 - [c80]Johannes Schäfer, Ulrich Heid, Roman Klinger:
Hierarchical Adversarial Correction to Mitigate Identity Term Bias in Toxicity Detection. WASSA 2024: 35-51 - [c79]Egil Rønningstad, Roman Klinger, Erik Velldal, Lilja Øvrelid:
Entity-Level Sentiment: More than the Sum of Its Parts. WASSA 2024: 84-96 - [c78]Patrick Bareiß, Roman Klinger, Jeremy Barnes:
English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts. WWW (Companion Volume) 2024: 1318-1326 - [e5]Orphée De Clercq, Valentin Barrière, Jeremy Barnes, Roman Klinger, João Sedoc, Shabnam Tafreshi:
Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, WASSA 2024, Bangkok, Thailand, August 15, 2024. Association for Computational Linguistics 2024, ISBN 979-8-89176-156-8 [contents] - [i61]Amelie Wührl, Yarik Menchaca Resendiz, Lara Grimminger, Roman Klinger:
What Makes Medical Claims (Un)Verifiable? Analyzing Entity and Relation Properties for Fact Verification. CoRR abs/2402.01360 (2024) - [i60]Patrick Bareiß, Roman Klinger, Jeremy Barnes:
English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts. CoRR abs/2402.03223 (2024) - [i59]Amelie Wührl, Dustin Wright, Roman Klinger, Isabelle Augenstein:
Understanding Fine-grained Distortions in Reports of Scientific Findings. CoRR abs/2402.12431 (2024) - [i58]Aswathy Velutharambath, Amelie Wührl, Roman Klinger:
Can Factual Statements be Deceptive? The DeFaBel Corpus of Belief-based Deception. CoRR abs/2403.10185 (2024) - [i57]Christopher Bagdon, Prathamesh Karmalkar, Harsha Gurulingappa, Roman Klinger:
"You are an expert annotator": Automatic Best-Worst-Scaling Annotations for Emotion Intensity Modeling. CoRR abs/2403.17612 (2024) - [i56]Egil Rønningstad, Roman Klinger, Erik Velldal, Lilja Øvrelid:
Entity-Level Sentiment: More than the Sum of Its Parts. CoRR abs/2407.03916 (2024) - [i55]Jan Hofmann, Cornelia Sindermann, Roman Klinger:
Prompt-based Personality Profiling: Reinforcement Learning for Relevance Filtering. CoRR abs/2409.04122 (2024) - [i54]Enrica Troiano, Sofie Labat, Marco Antonio Stranisci, Viviana Patti, Rossana Damiano, Roman Klinger:
Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing. CoRR abs/2409.19025 (2024) - [i53]Aswathy Velutharambath, Amelie Wührl, Roman Klinger:
How Entangled is Factuality and Deception in German? CoRR abs/2409.20165 (2024) - [i52]Johannes Schäfer, Aidan Combs, Christopher Bagdon, Jiahui Li, Nadine Probol, Lynn Greschner, Sean Papay, Yarik Menchaca Resendiz, Aswathy Velutharambath, Amelie Wührl, Sabine Weber, Roman Klinger:
Which Demographics do LLMs Default to During Annotation? CoRR abs/2410.08820 (2024) - 2023
- [j9]Enrica Troiano, Laura Oberländer, Roman Klinger:
Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction. Comput. Linguistics 49(1): 1-72 (2023) - [j8]Enrica Troiano, Aswathy Velutharambath, Roman Klinger:
From theories on styles to their transfer in text: Bridging the gap with a hierarchical survey. Nat. Lang. Eng. 29(4): 849-908 (2023) - [c77]Yarik Menchaca Resendiz, Roman Klinger:
Affective Natural Language Generation of Event Descriptions through Fine-grained Appraisal Conditions. INLG 2023: 375-387 - [c76]Aswathy Velutharambath, Roman Klinger:
UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection. WASSA@ACL 2023: 39-51 - [e4]Jeremy Barnes, Orphée De Clercq, Roman Klinger:
Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, WASSA@ACL 2023, Toronto, Canada, July 14, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-87-6 [contents] - [i51]Amelie Wührl, Lara Grimminger, Roman Klinger:
An Entity-based Claim Extraction Pipeline for Real-world Biomedical Fact-checking. CoRR abs/2304.05268 (2023) - [i50]Maximilian Wegge, Roman Klinger:
Automatic Emotion Experiencer Recognition. CoRR abs/2305.16731 (2023) - [i49]Aswathy Velutharambath, Roman Klinger:
UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection. CoRR abs/2306.02827 (2023) - [i48]Yarik Menchaca Resendiz, Roman Klinger:
Affective Natural Language Generation of Event Descriptions through Fine-grained Appraisal Conditions. CoRR abs/2307.14004 (2023) - [i47]Yarik Menchaca Resendiz, Roman Klinger:
Emotion-Conditioned Text Generation through Automatic Prompt Optimization. CoRR abs/2308.04857 (2023) - [i46]Roman Klinger:
Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approaches. CoRR abs/2309.02092 (2023) - [i45]Maximilian Wegge, Roman Klinger:
Topic Bias in Emotion Classification. CoRR abs/2312.09043 (2023) - 2022
- [c75]Amelie Wührl, Roman Klinger:
Entity-based Claim Representation Improves Fact-Checking of Medical Content in Tweets. ArgMining@COLING 2022: 187-198 - [c74]Flor Miriam Plaza del Arco, María Teresa Martín Valdivia, Roman Klinger:
Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora. COLING 2022: 6805-6817 - [c73]Sean Papay, Roman Klinger, Sebastian Padó:
Constraining Linear-chain CRFs to Regular Languages. ICLR 2022 - [c72]Isabelle Mohr, Amelie Wührl, Roman Klinger:
CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets. LREC 2022: 244-257 - [c71]Enrica Troiano, Laura Oberländer, Maximilian Wegge, Roman Klinger:
x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations. LREC 2022: 1365-1375 - [c70]Amelie Wührl, Roman Klinger:
Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on Twitter (BEAR). LREC 2022: 4439-4450 - [c69]Emils Kadikis, Vaibhav Srivastav, Roman Klinger:
Embarrassingly Simple Performance Prediction for Abductive Natural Language Inference. NAACL-HLT 2022: 6031-6037 - [c68]Anna Khlyzova, Carina Silberer, Roman Klinger:
On the Complementarity of Images and Text for the Expression of Emotions in Social Media. WASSA@ACL 2022: 1-15 - [c67]Valentino Sabbatino, Enrica Troiano, Antje Schweitzer, Roman Klinger:
"splink" is happy and "phrouth" is scary: Emotion Intensity Analysis for Nonsense Words. WASSA@ACL 2022: 37-50 - [c66]Anne Kreuter, Kai Sassenberg, Roman Klinger:
Items from Psychometric Tests as Training Data for Personality Profiling Models of Twitter Users. WASSA@ACL 2022: 315-323 - [e3]Jeremy Barnes, Orphée De Clercq, Valentin Barrière, Shabnam Tafreshi, Sawsan Alqahtani, João Sedoc, Roman Klinger, Alexandra Balahur:
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA@ACL 2022, Dublin, Ireland, May 26, 2022. Association for Computational Linguistics 2022, ISBN 978-1-955917-52-0 [contents] - [i44]Anna Khlyzova, Carina Silberer, Roman Klinger:
On the Complementarity of Images and Text for the Expression of Emotions in Social Media. CoRR abs/2202.07427 (2022) - [i43]Emils Kadikis, Vaibhav Srivastav, Roman Klinger:
Embarrassingly Simple Performance Prediction for Abductive Natural Language Inference. CoRR abs/2202.10408 (2022) - [i42]Anne Kreuter, Kai Sassenberg, Roman Klinger:
Items from Psychometric Tests as Training Data for Personality Profiling Models of Twitter Users. CoRR abs/2202.10415 (2022) - [i41]Valentino Sabbatino, Enrica Troiano, Antje Schweitzer, Roman Klinger:
"splink" is happy and "phrouth" is scary: Emotion Intensity Analysis for Nonsense Words. CoRR abs/2202.12132 (2022) - [i40]Enrica Troiano, Laura Oberländer, Maximilian Wegge, Roman Klinger:
x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations. CoRR abs/2203.10909 (2022) - [i39]Amelie Wührl, Roman Klinger:
Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on Twitter (BEAR). CoRR abs/2204.09952 (2022) - [i38]Isabelle Mohr, Amelie Wührl, Roman Klinger:
CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets. CoRR abs/2204.12164 (2022) - [i37]Enrica Troiano, Laura Oberländer, Roman Klinger:
Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction. CoRR abs/2206.05238 (2022) - [i36]Flor Miriam Plaza del Arco, María Teresa Martín Valdivia, Roman Klinger:
Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora. CoRR abs/2209.06701 (2022) - [i35]Amelie Wührl, Roman Klinger:
Entity-based Claim Representation Improves Fact-Checking of Medical Content in Tweets. CoRR abs/2209.07834 (2022) - [i34]Maximilian Wegge, Enrica Troiano, Laura Oberländer, Roman Klinger:
Experiencer-Specific Emotion and Appraisal Prediction. CoRR abs/2210.12078 (2022) - 2021
- [c65]Amelie Wührl, Roman Klinger:
Claim Detection in Biomedical Twitter Posts. BioNLP@NAACL-HLT 2021: 131-142 - [c64]Flor Miriam Plaza del Arco, Sercan Halat, Sebastian Padó, Roman Klinger:
Multi-Task Learning with Sentiment Emotion and Target Detection to Recognize Hate Speech and Offensive Language. FIRE (Working Notes) 2021: 297-318 - [c63]Enrica Troiano, Sebastian Padó, Roman Klinger:
Emotion Ratings: How Intensity, Annotation Confidence and Agreements are Entangled. WASSA@EACL 2021: 40-49 - [c62]Jan Hofmann, Enrica Troiano, Roman Klinger:
Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotations. WASSA@EACL 2021: 160-170 - [c61]Lara Grimminger, Roman Klinger:
Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection. WASSA@EACL 2021: 171-180 - [i33]Jan Hofmann, Enrica Troiano, Roman Klinger:
Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotations. CoRR abs/2102.12858 (2021) - [i32]Lara Grimminger, Roman Klinger:
Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection. CoRR abs/2103.01664 (2021) - [i31]Enrica Troiano, Sebastian Padó, Roman Klinger:
Emotion Ratings: How Intensity, Annotation Confidence and Agreements are Entangled. CoRR abs/2103.01667 (2021) - [i30]Amelie Wührl, Roman Klinger:
Claim Detection in Biomedical Twitter Posts. CoRR abs/2104.11639 (2021) - [i29]Sean Papay, Roman Klinger, Sebastian Padó:
Constraining Linear-chain CRFs to Regular Languages. CoRR abs/2106.07306 (2021) - [i28]Felix Casel, Amelie Heindl, Roman Klinger:
Emotion Recognition under Consideration of the Emotion Component Process Model. CoRR abs/2107.12895 (2021) - [i27]Bao Minh Doan Dang, Laura Oberländer, Roman Klinger:
Emotion Stimulus Detection in German News Headlines. CoRR abs/2107.12920 (2021) - [i26]Flor Miriam Plaza del Arco, Sercan Halat, Sebastian Padó, Roman Klinger:
Multi-Task Learning with Sentiment, Emotion, and Target Detection to Recognize Hate Speech and Offensive Language. CoRR abs/2109.10255 (2021) - [i25]Enrica Troiano, Aswathy Velutharambath, Roman Klinger:
From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Survey. CoRR abs/2110.15871 (2021) - 2020
- [b2]Roman Klinger:
Strukturierte Modellierung von Affekt in Text. University of Stuttgart, Germany, 2020 - [j7]Hendrik ter Horst, Matthias Hartung, Philipp Cimiano, Nicole Brazda, Hans Werner Müller, Roman Klinger:
Learning soft domain constraints in a factor graph model for template-based information extraction. Data Knowl. Eng. 125: 101764 (2020) - [c60]David Helbig, Enrica Troiano, Roman Klinger:
Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution Pipeline. SocialNLP@ACL 2020: 41-50 - [c59]Jan Hofmann, Enrica Troiano, Kai Sassenberg, Roman Klinger:
Appraisal Theories for Emotion Classification in Text. COLING 2020: 125-138 - [c58]Enrica Troiano, Roman Klinger, Sebastian Padó:
Lost in Back-Translation: Emotion Preservation in Neural Machine Translation. COLING 2020: 4340-4354 - [c57]Sean Papay, Roman Klinger, Sebastian Padó:
Dissecting Span Identification Tasks with Performance Prediction. EMNLP (1) 2020: 4881-4895 - [c56]Valentino Sabbatino, Laura Ana Maria Bostan, Roman Klinger:
Automatic Section Recognition in Obituaries. LREC 2020: 817-825 - [c55]Laura Ana Maria Bostan, Evgeny Kim, Roman Klinger:
GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception. LREC 2020: 1554-1566 - [c54]Thomas N. Haider, Steffen Eger, Evgeny Kim, Roman Klinger, Winfried Menninghaus:
PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry. LREC 2020: 1652-1663 - [c53]Laura Ana Maria Bostan, Roman Klinger:
Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus Detection. *SEM@COLING 2020: 58-70 - [i24]Valentino Sabbatino, Laura Ana Maria Bostan, Roman Klinger:
Automatic Section Recognition in Obituaries. CoRR abs/2002.12699 (2020) - [i23]Thomas N. Haider, Steffen Eger, Evgeny Kim, Roman Klinger, Winfried Menninghaus:
PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry. CoRR abs/2003.07723 (2020) - [i22]Jan Hofmann, Enrica Troiano, Kai Sassenberg, Roman Klinger:
Appraisal Theories for Emotion Classification in Text. CoRR abs/2003.14155 (2020) - [i21]David Helbig, Enrica Troiano, Roman Klinger:
Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution Pipeline. CoRR abs/2005.07617 (2020) - [i20]Sean Papay, Roman Klinger, Sebastian Padó:
Dissecting Span Identification Tasks with Performance Prediction. CoRR abs/2010.02587 (2020) - [i19]Laura Oberländer, Roman Klinger:
Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus Detection. CoRR abs/2010.07557 (2020) - [i18]Laura Oberländer, Kevin Reich, Roman Klinger:
Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions? CoRR abs/2011.01599 (2020)
2010 – 2019
- 2019
- [j6]Jeremy Barnes, Roman Klinger:
Embedding Projection for Targeted Cross-lingual Sentiment: Model Comparisons and a Real-World Study. J. Artif. Intell. Res. 66: 691-742 (2019) - [c52]Enrica Troiano, Sebastian Padó, Roman Klinger:
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English. ACL (1) 2019: 4005-4011 - [c51]Deniz Cevher, Sebastian Zepf, Roman Klinger:
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning. KONVENS 2019 - [c50]Evgeny Kim, Roman Klinger:
Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters. NAACL-HLT (1) 2019: 647-653 - [c49]Robert McHardy, Heike Adel, Roman Klinger:
Adversarial Training for Satire Detection: Controlling for Confounding Variables. NAACL-HLT (1) 2019: 660-665 - [c48]Laura Ana Maria Bostan, Roman Klinger:
Exploring Fine-Tuned Embeddings that Model Intensifiers for Emotion Analysis. WASSA@NAACL-HLT 2019: 25-34 - [e2]Alexandra Balahur, Roman Klinger, Véronique Hoste, Carlo Strapparava, Orphée De Clercq:
Proceedings of the Tenth Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA@NAACL-HLT 2019, Minneapolis, USA, June 6, 2019. Association for Computational Linguistics 2019 [contents] - [i17]Robert McHardy, Heike Adel, Roman Klinger:
Adversarial Training for Satire Detection: Controlling for Confounding Variables. CoRR abs/1902.11145 (2019) - [i16]Evgeny Kim, Roman Klinger:
Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters. CoRR abs/1903.12453 (2019) - [i15]Laura Ana Maria Bostan, Roman Klinger:
Exploring Fine-Tuned Embeddings that Model Intensifiers for Emotion Analysis. CoRR abs/1904.03164 (2019) - [i14]Enrica Troiano, Sebastian Padó, Roman Klinger:
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English. CoRR abs/1905.13618 (2019) - [i13]Evgeny Kim, Roman Klinger:
An Analysis of Emotion Communication Channels in Fan Fiction: Towards Emotional Storytelling. CoRR abs/1906.02402 (2019) - [i12]Jeremy Barnes, Roman Klinger:
Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World Study. CoRR abs/1906.10519 (2019) - [i11]Deniz Cevher, Sebastian Zepf, Roman Klinger:
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning. CoRR abs/1909.02764 (2019) - [i10]Laura Ana Maria Bostan, Evgeny Kim, Roman Klinger:
GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception. CoRR abs/1912.03184 (2019) - 2018
- [j5]Hanna Kicherer, Marcel Dittrich, Lukas Grebe, Christian Scheible, Roman Klinger:
What you use, not what you do: Automatic classification and similarity detection of recipes. Data Knowl. Eng. 117: 252-263 (2018) - [c47]Matthias Hartung, Hendrik ter Horst, Frank Grimm, Tim Diekmann, Roman Klinger, Philipp Cimiano:
SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling. ACL (4) 2018: 68-73 - [c46]Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde:
Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages. ACL (1) 2018: 2483-2493 - [c45]Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde:
Projecting Embeddings for Domain Adaption: Joint Modeling of Sentiment Analysis in Diverse Domains. COLING 2018: 818-830 - [c44]Evgeny Kim, Roman Klinger:
Who Feels What and Why? Annotation of a Literature Corpus with Semantic Roles of Emotions. COLING 2018: 1345-1359 - [c43]Laura Ana Maria Bostan, Roman Klinger:
An Analysis of Annotated Corpora for Emotion Classification in Text. COLING 2018: 2104-2119 - [c42]Florian Barth, Evgeny Kim, Sandra Murr, Roman Klinger:
A Reporting Tool for Relational Visualization and Analysis of Character Mentions in Literature. DHd 2018 - [c41]Manuel Braun, Roman Klinger, Sebastian Padó, Gabriel Viehhauser:
Digitale Modellierung von Figurenkomplexität am Beispiel des Parzival von Wolfram von Eschenbach. DHd 2018 - [c40]Florian Strohm, Roman Klinger:
An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs. DSAA 2018: 673-681 - [c39]Heike Adel, Laura Ana Maria Bostan, Sean Papay, Sebastian Padó, Roman Klinger:
DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction. EMNLP (Demonstration) 2018: 42-47 - [c38]Hendrik ter Horst, Matthias Hartung, Roman Klinger, Nicole Brazda, Hans Werner Müller, Philipp Cimiano:
Assessing the Impact of Single and Pairwise Slot Constraints in a Factor Graph Model for Template-Based Information Extraction. NLDB 2018: 179-190 - [c37]Camilo Thorne, Roman Klinger:
On the Semantic Similarity of Disease Mentions in MEDLINE and Twitter. NLDB 2018: 324-332 - [c36]Roman Klinger, Orphée De Clercq, Saif M. Mohammad, Alexandra Balahur:
IEST: WASSA-2018 Implicit Emotions Shared Task. WASSA@EMNLP 2018: 31-42 - [e1]Alexandra Balahur, Saif M. Mohammad, Véronique Hoste, Roman Klinger:
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA@EMNLP 2018, Brussels, Belgium, October 31, 2018. Association for Computational Linguistics 2018, ISBN 978-1-948087-80-3 [contents] - [i9]Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde:
Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages. CoRR abs/1805.09016 (2018) - [i8]Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde:
Projecting Embeddings for Domain Adaptation: Joint Modeling of Sentiment Analysis in Diverse Domains. CoRR abs/1806.04381 (2018) - [i7]Evgeny Kim, Roman Klinger:
A Survey on Sentiment and Emotion Analysis for Computational Literary Studies. CoRR abs/1808.03137 (2018) - [i6]Florian Strohm, Roman Klinger:
An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs. CoRR abs/1808.10653 (2018) - [i5]Roman Klinger, Orphée De Clercq, Saif M. Mohammad, Alexandra Balahur:
IEST: WASSA-2018 Implicit Emotions Shared Task. CoRR abs/1809.01083 (2018) - 2017
- [c35]Evgeny Kim, Sebastian Padó, Roman Klinger:
Prototypical Emotion Developments in Adventures, Romances, and Mystery Stories. DH 2017 - [c34]Nils Reiter, Sarah Schulz, Gerhard Kremer, Roman Klinger, Gabriel Viehhauser, Jonas Kuhn:
Teaching Computational Aspects in the Digital Humanities Program at University of Stuttgart - Intentions and Experiences. Teach4DH@GSCL 2017: 43-48 - [c33]Nicole Brazda, Hendrik ter Horst, Matthias Hartung, Cord Wiljes, Veronica Estrada, Roman Klinger, Wolfgang Kuchinke, Hans Werner Müller, Philipp Cimiano:
SCIO: An Ontology to Support the Formalization of Pre-Clinical Spinal Cord Injury Experiments. JOWO 2017 - [c32]Evgeny Kim, Sebastian Padó, Roman Klinger:
Investigating the Relationship between Literary Genres and Emotional Plot Development. LaTeCH@ACL 2017: 17-26 - [c31]Mario Sänger, Ulf Leser, Roman Klinger:
Fine-Grained Opinion Mining from Mobile App Reviews with Word Embedding Features. NLDB 2017: 3-14 - [c30]Hanna Kicherer, Marcel Dittrich, Lukas Grebe, Christian Scheible, Roman Klinger:
What You Use, Not What You Do: Automatic Classification of Recipes. NLDB 2017: 197-209 - [c29]Roman Klinger:
Does Optical Character Recognition and Caption Generation Improve Emotion Detection in Microblog Posts? NLDB 2017: 313-319 - [c28]Matthias Hartung, Roman Klinger, Franziska Schmidtke, Lars Vogel:
Identifying Right-Wing Extremism in German Twitter Profiles: A Classification Approach. NLDB 2017: 320-325 - [c27]Camilo Thorne, Roman Klinger:
Towards Confidence Estimation for Typed Protein-Protein Relation Extraction. BiomedicalNLP@RANLP 2017: 55-63 - [c26]Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde:
Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets. WASSA@EMNLP 2017: 2-12 - [c25]Hendrik Schuff, Jeremy Barnes, Julian Mohme, Sebastian Padó, Roman Klinger:
Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus. WASSA@EMNLP 2017: 13-23 - [c24]Matthias Hartung, Roman Klinger, Franziska Schmidtke, Lars Vogel:
Ranking Right-Wing Extremist Social Media Profiles by Similarity to Democratic and Extremist Groups. WASSA@EMNLP 2017: 24-33 - [c23]Maximilian Köper, Evgeny Kim, Roman Klinger:
IMS at EmoInt-2017: Emotion Intensity Prediction with Affective Norms, Automatically Extended Resources and Deep Learning. WASSA@EMNLP 2017: 50-57 - [i4]Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde:
Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets. CoRR abs/1709.04219 (2017) - [i3]Hendrik ter Horst, Matthias Hartung, Roman Klinger, Matthias Zwick, Philipp Cimiano:
Predicting Disease-Gene Associations using Cross-Document Graph-based Features. CoRR abs/1709.09239 (2017) - 2016
- [c22]Christian Scheible, Roman Klinger, Sebastian Padó:
Model Architectures for Quotation Detection. ACL (1) 2016 - [c21]Roman Klinger, Surayya Samat Suliya, Nils Reiter:
Automatic Emotion Detection for Quantitative Literary Studies. DH 2016: 826-828 - [c20]Jennifer Ling, Roman Klinger:
An Empirical, Quantitative Analysis of the Differences Between Sarcasm and Irony. ESWC (Satellite Events) 2016: 203-216 - [c19]Mario Sänger, Ulf Leser, Steffen Kemmerer, Peter Adolphs, Roman Klinger:
SCARE ― The Sentiment Corpus of App Reviews with Fine-grained Annotations in German. LREC 2016 - [i2]Janik Jaskolski, Fabian Siegberg, Thomas Tibroni, Philipp Cimiano, Roman Klinger:
Opinion Mining in Online Reviews About Distance Education Programs. CoRR abs/1607.06299 (2016) - 2015
- [c18]Roman Klinger, Philipp Cimiano:
Instance Selection Improves Cross-Lingual Model Training for Fine-Grained Sentiment Analysis. CoNLL 2015: 153-163 - [c17]Wiltrud Kessler, Roman Klinger, Jonas Kuhn:
Towards Opinion Mining from Reviews for the Prediction of Product Rankings. WASSA@EMNLP 2015: 51-57 - 2014
- [c16]Benjamin Paassen, Andreas Stöckel, Raphael Dickfelder, Jan Philip Göpfert, Nicole Brazda, Tarek Kirchhoffer, Hans Werner Müller, Roman Klinger, Matthias Hartung, Philipp Cimiano:
Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments. SWAIE@COLING 2014: 25-32 - [c15]Matthias Hartung, Roman Klinger, Matthias Zwick, Philipp Cimiano:
Towards Gene Recognition from Rare and Ambiguous Abbreviations using a Filtering Approach. BioNLP@ACL 2014: 118-127 - [c14]Roman Klinger, Philipp Cimiano:
The USAGE review corpus for fine grained multi lingual opinion analysis. LREC 2014: 2211-2218 - [c13]Konstantin Buschmeier, Philipp Cimiano, Roman Klinger:
An Impact Analysis of Features in a Classification Approach to Irony Detection in Product Reviews. WASSA@ACL 2014: 42-49 - [i1]Shweta Bagewadi Kawalia, Tamara Bobic, Martin Hofmann-Apitius, Juliane Fluck, Roman Klinger:
Detecting miRNA Mentions and Relations in Biomedical Literature. F1000Research 3: 205 (2014) - 2013
- [j4]Tamara Bobic, Roman Klinger:
Committee-based Selection of Weakly Labeled Instances for Learning Relation Extraction. Res. Comput. Sci. 70: 187-197 (2013) - [c12]Roman Klinger, Philipp Cimiano:
Bi-directional Inter-dependencies of Subjective Expressions and Targets and their Value for a Joint Model. ACL (2) 2013: 848-854 - [c11]John Philip McCrae, Philipp Cimiano, Roman Klinger:
Orthonormal Explicit Topic Analysis for Cross-Lingual Document Matching. EMNLP 2013: 1732-1740 - [c10]Roman Klinger, Philipp Cimiano:
Joint and Pipeline Probabilistic Models for Fine-Grained Sentiment Analysis: Extracting Aspects, Subjective Phrases and their Relations. ICDM Workshops 2013: 937-944 - 2012
- [c9]Roman Klinger, Philipp Senger, Sumit Madan, Michal Jacovi:
Online Communities Support Policy-Making: The Need for Data Analysis. ePart 2012: 132-143 - [c8]Fotis Aisopos, Magdalini Kardara, Philipp Senger, Roman Klinger, Athanasios Papaoikonomou, Konstantinos Tserpes, Michael Gardner, Theodora A. Varvarigou:
E-Government and Policy Simulation in Intelligent Virtual Environments. WEBIST 2012: 129-135 - 2011
- [b1]Roman Klinger:
Conditional random fields for named entity recognition: feature selection and optimization in biology and chemistry. Dortmund University of Technology, 2011, ISBN 978-3-8440-0213-3, pp. 1-180 - [j3]Philippe E. Thomas, Roman Klinger, Laura Inés Furlong, Martin Hofmann-Apitius, Christoph M. Friedrich:
Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers. BMC Bioinform. 12(S-4): S4 (2011) - [c7]Roman Klinger:
Automatically Selected Skip Edges in Conditional Random Fields for Named Entity Recognition. RANLP 2011: 580-585 - 2010
- [c6]Bernd Müller, Roman Klinger, Harsha Gurulingappa, Heinz-Theodor Mevissen, Martin Hofmann-Apitius, Juliane Fluck, Christoph M. Friedrich:
Abstracts versus Full Texts and Patents: A Quantitative Analysis of Biomedical Entities. IRFC 2010: 152-165 - [c5]Harsha Gurulingappa, Bernd Müller, Roman Klinger, Heinz-Theodor Mevissen, Martin Hofmann-Apitius, Christoph M. Friedrich, Juliane Fluck:
Prior Art Search in Chemistry Patents Based On Semantic Concepts and Co-Citation Analysis. TREC 2010
2000 – 2009
- 2009
- [j2]Corinna Kolárik, Roman Klinger, Martin Hofmann-Apitius:
Identification of histone modifications in biomedical text for supporting epigenomic research. BMC Bioinform. 10(S-1) (2009) - [c4]Roman Klinger, Christoph M. Friedrich:
Feature Subset Selection in Conditional Random Fields for Named Entity Recognition. RANLP 2009: 185-191 - [c3]Roman Klinger, Christoph M. Friedrich:
User's Choice of Precision and Recall in Named Entity Recognition. RANLP 2009: 192-196 - [c2]Harsha Gurulingappa, Bernd Müller, Roman Klinger, Heinz-Theodor Mevissen, Martin Hofmann-Apitius, Juliane Fluck, Christoph M. Friedrich:
Patent Retrieval in Chemistry Based on Semantically Tagged Named Entities. TREC 2009 - 2008
- [c1]Roman Klinger, Corinna Kolárik, Juliane Fluck, Martin Hofmann-Apitius, Christoph M. Friedrich:
Detection of IUPAC and IUPAC-like chemical names. ISMB 2008: 268-276 - 2007
- [j1]Roman Klinger, Christoph M. Friedrich, Heinz-Theodor Mevissen, Juliane Fluck, Martin Hofmann-Apitius, Laura Inés Furlong, Ferran Sanz:
Identifying gene-Specific Variations in Biomedical Text. J. Bioinform. Comput. Biol. 5(6): 1277-1296 (2007)
Coauthor Index
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