Bagdon, Christopher Doyle et al. (2024): “You are an expert annotator”: Automatic Best–Worst-Scaling Annotations for Emotion Intensity Modeling. In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Mexico City, Mexico: Association for Computational Linguistics. S. 7917–7929.

Bareiss, Patrick/Klinger, Roman/Barnes, Jeremy (2024): English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts. In: WWW ’24: Companion Proceedings of the ACM on Web Conference 2024. New York. S. 1318–1326.

Rønningstad, Egil et al. (2024): Entity-Level Sentiment: More than the Sum of Its Parts. In: Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis. Bangkok, Thailand: Association for Computational Linguistics. S. 84–96.

Schäfer, Johannes/Heid, Ulrich/Klinger, Roman (2024): Hierarchical Adversarial Correction to Mitigate Identity Term Bias in Toxicity Detection. In: Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis. Bangkok, Thailand: Association for Computational Linguistics. S. 35–51.

Troiano, Enrica et al. (2024): Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing. In: Findings of the Association for Computational Linguistics: EMNLP 2024. Miami, Florida: Association for Computational Linguistics. S. 1634–1658.

Velutharambath, Aswathy/Klinger, Roman (2024): Can Factual Statements Be Deceptive?: The DeFaBel Corpus of Belief-based Deception. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ACL. S. 2708–2723.

Velutharambath, Aswathy/Wuehrl, Amelie/Klinger, Roman (2024): How Entangled is Factuality and Deception in German?. In: Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics. S. 9538–9554.

Wegge, Maximilian/Klinger, Roman (2024): Topic Bias in Emotion Classification. In: Proceedings of the Ninth Workshop on Noisy and User-generated Text (W-NUT 2024). San Ġiljan, Malta: Association for Computational Linguistics. S. 89–103.

Wemmer, Eileen/Labat, Sofie/Klinger, Roman (2024): EmoProgress: Cumulated Emotion Progression Analysis in Dreams and Customer Service Dialogues. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Torino, Italia: ELRA and ICCL. S. 5660–5677.

Wuehrl, Amelie et al. (2024a): IMS_medicALY at #SMM4H 2024: Detecting Impacts of Outdoor Spaces on Social Anxiety with Data Augmented Ensembling. In: Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks. Bangkok, Thailand: Association for Computational Linguistics. S. 83–87.

Wuehrl, Amelie et al. (2024b): Understanding Fine-grained Distortions in Reports of Scientific Findings. In: Findings of the Association for Computational Linguistics ACL 2024. Bangkok, Thailand and virtual meeting: Association for Computational Linguistics. S. 6175–6191.

Wührl, Amelie et al. (2024): What Makes Medical Claims (Un)Verifiable?: Analyzing Entity and Relation Properties for Fact Verification. In: Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics. S. 1–13.

Combs, Aidan et al. (2023a): The effect of occupational status on health: Putting the social in socioeconomic status. In: Heliyon 9.

Combs, Aidan et al. (2023b): Perceived gender and political persuasion: a social media field experiment during the 2020 US Democratic presidential primary election. In: Scientific Reports 13.

Combs, Aidan et al. (2023c): Reducing political polarization in the United States with a mobile chat platform. In: Nature Human Behaviour 7, S. 1454–1461.

Klinger, Roman (2023a): Where are We in Event-centric Emotion Analysis?: Bridging Emotion Role Labeling and Appraisal-based Approaches. In: Proceedings of the Big Picture Workshop. Singapore: Association for Computational Linguistics. S. 1–17.

Klinger, Roman (2023b): Emotionsklassifikation in Texten unter Berücksichtigung des Komponentenprozessmodells. In: Jaki, Sylvia/Steiger, Stefan (Hg.): Digitale Hate Speech: interdisziplinäre Perspektiven auf Erkennung, Beschreibung und Regulation. Berlin, Heidelberg: J.B. Metzler. S. 131–154.

Menchaca Resendiz, Yarik/Klinger, Roman (2023a): Emotion-Conditioned Text Generation through Automatic Prompt Optimization. In: Proceedings of the 1st Workshop on Taming Large Language Models: Controllability in the era of Interactive Assistants! Prag: Association for Computational Linguistics. S. 24–30.

Menchaca Resendiz, Yarik/Klinger, Roman (2023b): Affective Natural Language Generation of Event Descriptions through Fine-grained Appraisal Conditions. In: Proceedings of the 16th International Natural Language Generation Conference. Prag: Association for Computational Linguistics. S. 375–387.

Troiano, Enrica/Klinger, Roman/Padó, Sebastian (2023): On the Relationship between Frames and Emotionality in Text. In: Northern European Journal of Language Technology 9.

Troiano, Enrica/Oberländer, Laura/Klinger, Roman (2023): Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction. In: Computational linguistics 49, S. 1–72.

Velutharambath, Aswathy/Klinger, Roman (2023): UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection. In: Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis. Toronto: Association for Computational Linguistics. S. 39–51.

Velutharambath, Aswathy/Sassenberg, Kai/Klinger, Roman (2023): Prevention or Promotion?: Predicting Author’s Regulatory Focus. In: Northern European Journal of Language Technology 9.

Wegge, Maximilian/Klinger, Roman (2023): Automatic Emotion Experiencer Recognition. In: Proceedings of the 3rd Workshop on Computational Linguistics for the Political and Social Sciences. Ingolstadt: Association for Computational Lingustics. S. 1–7.

Wührl, Amelie/Grimminger, Lara/Klinger, Roman (2023): An Entity-based Claim Extraction Pipeline for Real-world Biomedical Fact-checking. In: Proceedings of the Sixth Fact Extraction and VERification Workshop (FEVER). Dubrovnik: Association for Computational Linguistics. S. 29–37.

Štajner, Sanja/Klinger, Roman (2023): Emotion Analysis from Texts. In: Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts. Dubrovnik: Association for Computational Linguistics. S. 7–12.

(2022): Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Dublin: Association for Computational Linguistics.

Kadiķis, Emīls/Srivastav, Vaibhav/Klinger, Roman (2022): Embarrassingly Simple Performance Prediction for Abductive Natural Language Inference. In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Seattle: Association for Computational Linguistics. S. 6031–6037.

Khlyzova, Anna/Silberer, Carina/Klinger, Roman (2022): On the Complementarity of Images and Text for the Expression of Emotions in Social Media. In: Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Association for Computational Linguistics. S. 1–15.

Kreuter, Anne/Sassenberg, Kai/Klinger, Roman (2022): Items from Psychometric Tests as Training Data for Personality Profiling Models of Twitter Users. In: Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Dublin: Association for Computational Linguistics. S. 315–323.

Li, Tianyi et al. (2022a): Language Models Are Poor Learners of Directional Inference. In: Findings of the Association for Computational Linguistics: EMNLP 2022. Association for Computational Linguistics. S. 903–921.

Li, Tianyi et al. (2022b): Cross-lingual Inference with A Chinese Entailment Graph. In: Findings of the Association for Computational Linguistics: ACL 2022. Association for Computational Linguistics. S. 1214–1233.

Mohr, Isabelle/Wührl, Amelie/Klinger, Roman (2022): CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets. In: Proceedings of the Thirteenth Language Resources and Evaluation Conference. Marseille: European Language Resources Association. S. 244–257.

Papay, Sean/Klinger, Roman/Padó, Sebastian (2022): Constraining Linear-chain CRFs to Regular Languages. arxiv.

Plaza-del-Arco, Flor Miriam/Martín-Valdivia, María-Teresa/Klinger, Roman (2022): Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora. In: Proceedings of the 29th International Conference on Computational Linguistics. Gyeongju: International Committee on Computational Linguistics. S. 6805–6817.

Sabbatino, Valentino et al. (2022): “splink” is happy and “phrouth” is scary: Emotion Intensity Analysis for Nonsense Words. In: Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Dublin: Association for Computational Linguistics. S. 37–50.

Troiano, Enrica et al. (2022): x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations. In: Proceedings of the Thirteenth Language Resources and Evaluation Conference. Marseille: European Language Resources Association. S. 1365–1375.

Troiano, Enrica/Velutharambath, Aswathy/Klinger, Roman (2022): From theories on styles to their transfer in text: Bridging the gap with a hierarchical survey. In: Natural Language Engineering 29, S. 849–908.

Wegge, Maximilian et al. (2022): Experiencer-Specific Emotion and Appraisal Prediction. In: Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS). Abu Dhabi: Association for Computational Linguistics. S. 25–32.

Wührl, Amelie/Klinger, Roman (2022a): Recovering Patient Journeys: A Corpus of Biomedical Entities and Relations on Twitter (BEAR). In: Proceedings of the Thirteenth Language Resources and Evaluation Conference. Marseille: European Language Resources Association. S. 4439–4450.

Wührl, Amelie/Klinger, Roman (2022b): Entity-based Claim Representation Improves Fact-Checking of Medical Content in Tweets. In: Proceedings of the 9th Workshop on Argument Mining. Gyeongju: International Conference on Computational Linguistics. S. 187–198.

Casel, Felix/Heindl, Amelie/Klinger, Roman (2021): Emotion Recognition under Consideration of the Emotion Component Process Model. In: Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021). KONVENS 2021 Organizers. S. 49–61.

Doan Dang, Bao Minh/Oberländer, Laura Ana Maria/Klinger, Roman (2021): Emotion Stimulus Detection in German News Headlines. In: Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021). KONVENS 2021 Organizers. S. 73–85.

Grimminger, Lara/Klinger, Roman (2021): Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection. In: Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics. S. 171–180.

Hofmann, Jan/Troiano, Enrica/Klinger, Roman (2021): Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotations. In: Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics. S. 160–170.

Plaza-del-Arco, Flor Miriam et al. (2021): Multi-Task Learning with Sentiment, Emotion, and Target Detection to Recognize Hate Speech and Offensive Language. In: Working Notes of FIRE 2021: Forum for Information Retrieval Evaluation Gandhinagar, India, December 13-17, 2021. S. 297–318. (= CEUR Workshop Proceedings).

Troiano, Enrica/Padó, Sebastian/Klinger, Roman (2021): Emotion Ratings: How Intensity, Annotation Confidence and Agreements are Entangled. In: Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics. S. 40–49.

Weber, Sabine/Steedman, Mark (2021a): Zero-Shot Cross-Lingual Transfer is a Hard Baseline to Beat in German Fine-Grained Entity Typing. In: Proceedings of the Second Workshop on Insights from Negative Results in NLP. Association for Computational Linguistics. S. 42–48.

Weber, Sabine/Steedman, Mark (2021b): Fine-grained General Entity Typing in German using GermaNet. In: Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15). Association for Computational Linguistics. S. 138–143.

Wührl, Amelie/Klinger, Roman (2021a): Claim Detection in Biomedical Twitter Posts. In: Proceedings of the 20th Workshop on Biomedical Language Processing. Association for Computational Linguistics. S. 131–142.

Wührl, Amelie/Klinger, Roman (2021b): Claim Detection in Biomedical Twitter Posts as a Prerequisite for Fact-Checking. In: Proceedings of the BioNLP 2021 workshop. Association for Computational Linguistics.

(2020): Proceedings of LREC2020 Workshop “People in language, vision and the mind” (ONION2020). Marseille, France: European Language Resources Association (ELRA). S. i–vii.

Armbrust, Felix/Schäfer, Henry/Klinger, Roman (2020): A Computational Analysis of Financial and Environmental Narratives within Financial Reports and its Value for Investors. In: Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation. COLING. S. 181–194.

Bail, Christopher A. et al. (2020): Assessing the Russian Internet Research Agency’s impact on the political attitudes and behaviors of American Twitter users in late 2017. In: Proceedings of the National Academy of Sciences of the United States of America 117, S. 243–250.

Bostan, Laura Ana Maria/Kim, Evgeny/Klinger, Roman (2020): GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception. In: LREC 2020 Marseille: Twelfth International Conference on Language Resources and Evaluation, May 11-16, 2020, Palais du Pharo, Marseille, France: conference proceedings. Paris: European Language Resources Association. S. 1554–1566.

Haider, Thomas et al. (2020): PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry. In: Proceedings of the Twelfth Language Resources and Evaluation Conference. S. 1652–1663.

Helbig, David/Troiano, Enrica/Klinger, Roman (2020): Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution Pipeline. In: Proceedings of the Eighth International Workshop on Natural Language Processing for Social Media. Association for Computational Linguistics. S. 41–50.

Hofmann, Jan et al. (2020): Appraisal Theories for Emotion Classification in Text. In: Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics. S. 125–138.

Klinger, Roman (2020): Strukturierte Modellierung von Affekt in Text. Stuttgart.

Klinger, Roman/Kim, Evgeny/Padó, Sebastian (2020): Emotion Analysis for Literary Studies. In: Reiter, Nils/Pichler, Axel/Kuhn, Jonas (Hg.): Reflektierte algorithmische Textanalyse: Interdisziplinäre(s) Arbeiten in der CRETA-Werkstatt. Berlin, Boston: De Gruyter. S. 237–268.

Oberländer, Laura Ana Maria/Klinger, Roman (2020): Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus Detection. In: Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics. Association for Computational Linguistics. S. 58–70.

Oberländer, Laura/Reich, Kevin/Klinger, Roman (2020): Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?. In: Proceedings of the Third Workshop on Computational Modeling of People’s Opinions, Personality, and Emotion’s in Social Media. Association for Computational Linguistics. S. 119–128.

Papay, Sean/Klinger, Roman/Padó, Sebastian (2020): Dissecting Span Identification Tasks with Performance Prediction. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics. S. 4881–4895.

Sabbatino, Valentino/Bostan, Laura Ana Maria/Klinger, Roman (2020): Automatic Section Recognition in Obituaries. In: Proceedings of the Twelfth Language Resources and Evaluation Conference. S. 817–825.

Troiano, Enrica/Klinger, Roman/Padó, Sebastian (2020): Lost in Back-Translation: Emotion Preservation in Neural Machine Translation. In: Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics. S. 4340–4354.

(2019): Proceedings of the Tenth Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Minneapolis: Association for Computational Linguistics.

Barnes, Jeremy/Klinger, Roman (2019): Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World Study. In: Journal of artificial intelligence research 66, S. 691–742.

Bostan, Laura/Klinger, Roman (2019): Exploring fine-tuned embeddings that model intensifiers for emotion analysis. In: Proceedings of the Tenth Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Minneapolis: Association for Computational Linguistics. S. 25–34.

Cevher, Deniz/Zepf, Sebastian/Klinger, Roman (2019): Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning. In: Proceedings of the 15th Conference on Natural Language Processing (KONVENS 2019). German Society for Computational Linguistics & Language Technology. S. 79–90.

Combs, Aidan et al. (2019): Fast approximate STEM image simulations from a machine learning model. In: Advanced Structural and Chemical Imaging 5.

Horst, Hendrik ter et al. (2019): Learning soft domain constraints in a factor graph model for template-based information extraction. In: Data & Knowledge Engineering 125, S. 101764.

Kim, Evgeny/Klinger, Roman (2019a): Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics. S. 647–653.

Kim, Evgeny/Klinger, Roman (2019b): An Analysis of Emotion Communication Channels in Fan-Fiction: Towards Emotional Storytelling. In: Proceedings of the Second Workshop on Storytelling. Association for Computational Linguistics. S. 56–64.

Kim, Evgeny/Klinger, Roman (2019c): A Survey on Sentiment and Emotion Analysis for Computational Literary Studies. In: Zeitschrift für digitale Geisteswissenschaften, S. 1–23.

McHardy, Robert/Adel, Heike/Klinger, Roman (2019): Adversarial Training for Satire Detection: Controlling for Confounding Variables. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics. S. 660–665.

Troiano, Enrica/Padó, Sebastian/Klinger, Roman (2019): Crowdsourcing and Validating Event-focused Emotion Corpora for German and English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. S. 4005–4011.

Weber, Sabine/Steedman, Mark (2019): Construction and Alignment of Multilingual Entailment Graphs for Semantic Inference. In: Proceedings of the 2019 Workshop on Widening NLP. Association for Computational Linguistics. S. 77–79.

(2018): Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Brüssel: Association for Computational Linguistics.

Adel, Heike et al. (2018): DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Association for Computational Linguistics.

Barnes, Jeremy/Klinger, Roman/Schulte im Walde, Sabine (2018a): Projecting Embeddings for Domain Adaption: Joint Modeling of Sentiment Analysis in Diverse Domains. In: Proceedings of the 27th International Conference on Computational Linguistics. Association for Computational Linguistics. S. 818–830.

Barnes, Jeremy/Klinger, Roman/Schulte im Walde, Sabine (2018b): Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Melbourne: Association for Computational Linguistics. S. 2483–2493.

Barth, Florian et al. (2018): A Reporting Tool for Relational Visualization and Analysis of Character Mentions in Literature. In: Kritik der digitalen Vernunft: Konferenzabstracts: Universität zu Köln, 26. Februar bis 2. März 2018.

Bostan, Laura Ana Maria/Klinger, Roman (2018): An Analysis of Annotated Corpora for Emotion Classification in Text. In: Proceedings of the 27th International Conference on Computational Linguistics. Santa Fe, New Mexico: Association for Computational Linguistics. S. 2104–2119.

Braun, Manuel et al. (2018): Digitale Modellierung von Figurenkomplexität am Beispiel des Parzival von Wolfram von Eschenbach. In: Kritik der digitalen Vernunft: Konferenzabstracts: Universität zu Köln, 26. Februar bis 2. März 2018.

Fähndrich, Johannes/Weber, Sabine/Kanthak, Hannes (2018): A Marker Passing Approach to Winograd Schemas. In: Semantic technology: 8th joint international conference, JIST 2018, Awaji, Japan, November 26–28, 2018, proceedings. Cham, Switzerland: Springer International Publishing. S. 165–181.

Hartung, Matthias et al. (2018): SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling. In: Proceedings of ACL 2018, System Demonstrations. Association for Computational Linguistics. S. 68–73.

Kicherer, Hanna et al. (2018): What You Use, Not What You Do: Automatic Classification and Similarity Detection of Recipes. In: Data and Knowledge Engineering 117, S. 252–263.

Kim, Evgeny/Klinger, Roman (2018): Who Feels What and Why?: Annotation of a Literature Corpus with Semantic Roles of Emotions. In: Proceedings of the 27th International Conference on Computational Linguistics. Association for Computational Linguistics. S. 1345–1359.

Klinger, Roman et al. (2018): IEST: WASSA-2018 Implicit Emotions Shared Task. In: Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Brüssel: Association for Computational Linguistics. S. 31–42.

Srivastava, Ankit et al. (2018): Different German and English Coreference Resolution Models for Multi-domain Content Curation Scenarios. In: Language Technologies for the Challenges of the Digital Age: 27th International Conference, GSCL 2017, Berlin, Germany, September 13-14, 2017, Proceedings. Springer International Publishing. S. 48–61.

Strohm, Florian/Klinger, Roman (2018): An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs. In: 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). Piscataway, NJ: IEEE.

Ter Horst, Hendrik et al. (2018): Assessing the Impact of Single and Pairwise Slot Constraints in a Factor Graph Model for Template-Based Information Extraction. In: Natural Language Processing and Information Systems: 23rd International Conference on Applications of Natural Language to Information Systems, NLDB 2018, Paris, France, June 13-15, 2018, Proceedings. Cham: Springer International Publishing. S. 179–190. (= Lecture Notes in Computer Science 10859).

Thorne, Camilo/Klinger, Roman (2018): On the Semantic Similarity of Disease Mentions in MEDLINE and Twitter. In: Natural Language Processing and Information Systems: 23rd International Conference on Applications of Natural Language to Information Systems, NLDB 2018, Paris, France, June 13-15, 2018, Proceedings. Cham: Springer International Publishing. S. 324–332.

Barnes, Jeremy/Klinger, Roman/Schulte im Walde, Sabine (2017): Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets. In: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics. S. 2–12.

Hartung, Matthias et al. (2017a): Identifying Right-Wing Extremism in German Twitter Profiles: A Classification Approach. In: Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings. Cham: Springer International Publishing. S. 320–325.

Hartung, Matthias et al. (2017b): Ranking Right-Wing Extremist Social Media Profiles by Similarity to Democratic and Extremist Groups. In: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics. S. 24–33.

Kicherer, Hanna et al. (2017): What You Use, Not What You Do: Automatic Classification of Recipes. In: Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings. Cham: Springer International Publishing. S. 197–209.

Kim, Evgeny/Padó, Sebastian/Klinger, Roman (2017): Investigating the Relationship between Literary Genres and Emotional Plot Development. In: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Association for Computational Linguistics. S. 17–26.

Klinger, Roman (2017): Does Optical Character Recognition and Caption Generation Improve Emotion Detection in Microblog Posts?. In: Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings. Cham: Springer International Publishing. S. 313–319.

Köper, Maximilian/Kim, Evgeny/Klinger, Roman (2017): IMS at EmoInt-2017: Emotion Intensity Prediction with Affective Norms, Automatically Extended Resources and Deep Learning. In: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics.

Reiter, Nils et al. (2017): Teaching Computational Aspects in the Digital Humanities Program at University of Stuttgart: Intentions and Experiences. In: Proceedings of the Workshop on Teaching NLP for Digital Humanities (Teach4DH 2017) co-located with GSCL 2017. S. 43–48. (= CEUR Workshop Proceedings 1918).

Schuff, Hendrik et al. (2017): Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus. In: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics. S. 13–23.

Sänger, Mario/Leser, Ulf/Klinger, Roman (2017): Fine-Grained Opinion Mining from Mobile App Reviews with Word Embedding Features. In: Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings. Cham: Springer International Publishing. S. 3–14.

Thorne, Camilo/Klinger, Roman (2017): Towards Confidence Estimation for typed Protein-Protein Relation Extraction. In: Proceedings of the Biomedical NLP Workshop associated with RANLP 2017. Association for Computational Linguistics. S. 55–63.

Klinger, Roman/Suliya, Surayya Samat/Reiter, Nils (2016): Automatic Emotion Detection for Quantitative Literary Studies: A case study based on Franz Kafka’s “Das Schloss” and “Amerika”. In: Digital Humanities 2016: Conference Abstracts. Jagiellonian University and Pedagogical University. S. 826–828.

Ling, Jennifer/Klinger, Roman (2016): An Empirical, Quantitative Analysis of the Differences Between Sarcasm and Irony. In: The Semantic Web: ESWC 2016 Satellite Events, Heraklion, Crete, Greece, May 29 – June 2, 2016. Revised Selected Papers. Cham: Springer International Publishing. S. 203–216.

Scheible, Christian/Klinger, Roman/Padó, Sebastian (2016): Model Architectures for Quotation Detection. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. S. 1736–1745.

Sänger, Mario et al. (2016): SCARE: the Sentiment Corpus of App Reviews with Fine-grained Annotations in German. In: Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). European Language Resources Association (ELRA). S. 1114–1121.

Bagewadi, Shweta et al. (2015): Detecting miRNA Mentions and Relations in Biomedical Literature [version 3; peer review: 2 approved, 1 approved with reservations]. In: F1000Research 3, S. 1–36.

Kessler, Wiltrud/Klinger, Roman/Kuhn, Jonas (2015): Towards Opinion Mining from Reviews for the Prediction of Product Rankings. In: Proceedings of the 6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Lisboa, Portugal: Association for Computational Linguistics. S. 51–57.

Klinger, Roman/Cimiano, Philipp (2015): Instance Selection Improves Cross-Lingual Model Training for Fine-Grained Sentiment Analysis. In: Proceedings of the Nineteenth Conference on Computational Natural Language Learning. Association for Computational Linguistics. S. 153–163.

Buschmeier, Konstantin/Cimiano, Philipp/Klinger, Roman (2014): An Impact Analysis of Features in a Classification Approach to Irony Detection in Product Reviews. In: Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Baltimore, Maryland: Association for Computational Linguistics. S. 42–49.

Hartung, Matthias et al. (2014): Towards Gene Recognition from Rare and Ambiguous Abbreviations using a Filtering Approach. In: Proceedings of BioNLP 2014. Baltimore, Maryland: Association for Computational Linguistics. S. 118–127.

Klinger, Roman/Cimiano, Philipp (2014): The USAGE review corpus for fine grained multi lingual opinion analysis. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14). Reykjavik, Iceland: European Language Resources Association (ELRA). S. 2211–2218.

Paassen, Benjamin et al. (2014): Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments. In: Proceedings of the Third Workshop on Semantic Web and Information Extraction. S. 25–32.

Bobic, Tamara/Klinger, Roman (2013): Committee-based Selection of Weakly Labeled Instances for Learning Relation Extraction. In: Research in Computing Science 70, S. 187–197.

Klinger, Roman/Cimiano, Philipp (2013a): Joint and Pipeline Probabilistic Models for Fine-Grained Sentiment Analysis: Extracting Aspects, Subjective Phrases and their Relations. In: ICDMW ’13: Proceedings of the 2013 IEEE 13th International Conference on Data Mining Workshops. IEEE. S. 937–944.

Klinger, Roman/Cimiano, Philipp (2013b): Bi-directional Inter-dependencies of Subjective Expressions and Targets and their Value for a Joint Model. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics. Sofia, Bulgaria: Association for Computational Linguistics. S. 848–854.

McCrae, John Philip/Cimiano, Philipp/Klinger, Roman (2013): Orthonormal Explicit Topic Analysis for Cross-Lingual Document Matching. In: Proceedings of the 2013 Conference on Empirical Natural Language Processing. Seattle, Washington: Association for Computational Linguistics. S. 1732–1740.

Aisopos, Fotis et al. (2012): E-Government and Policy Simulation in Intelligent Virtual Environments. In: Proceedings of the 8th International Conference on Web Information Systems and Technologies: Porto, Portugal, 18 - 21 April, 2012. SciTePress. S. 129–135.

Bobić, Tamara et al. (2012): Improving Distantly Supervised Extraction of Drug-Drug and Protein-Protein Interactions. In: Proceedings of the Joint Workshop on Unsupervised and Semi-Supervised Learning in NLP. Association for Computational Linguistics. S. 35–43.

Klinger, Roman et al. (2012): Online Communities Support Policy-Making: The Need for Data Analysis. In: Electronic participation: 4th IFIP WG 8.5 international conference; proceedings / EPart 2012, Kristiansand, Norway, September 3 - 5, 2012. Berlin ; Heidelberg: Springer. S. 132–143. (= Lecture Notes in Computer Science 7444).

Klinger, Roman (2011a): Conditional Random Fields for Named Entity Recognition - Feature Selection and Optimization in Biology and Chemistry. Aachen, Germany: Shaker.

Klinger, Roman (2011b): Automatically Selected Skip Edges in Conditional Random Fields for Named Entity Recognition. In: Proceedings of the International Conference Recent Advances in Natural Language Processing 2011. Hissar: Association for Computational Linguistics. S. 580–585.

Klinger, Roman/Riedel, Sebastian/McCallum, Andrew (2011): Inter-Event Dependencies support Event Extraction from Biomedical Literature.

Thomas, Philippe E. et al. (2011a): Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers. In: BMC Bioinformatics 12, S. 1–18.

Thomas, Philippe et al. (2011b): Learning to Extract Protein-Protein Interactions using Distant Supervision. In: Proceedings of Workshop on Robust Unsupervised and Semisupervised Methods in Natural Language Processing. Hissar, Bulgaria: Association for Computational Linguistics. S. 25–32.

Gurulingappa, Harsha et al. (2010): An Empirical Evaluation of Resources for the Identification of Diseases and Adverse Effects in Biomedical Literature. In: 2nd Workshop on Building and evaluating resources for biomedical text mining (7th edition of the Language Resources and Evaluation Conference).

Müller, Bernd et al. (2010): Abstracts versus Full Texts and Patents: A Quantitative Analysis of Biomedical Entities. In: Advances in Multidisciplinary Retrieval: First Information Retrieval Facility Conference, IRFC 2010, Vienna, Austria, May 31, 2010, Proceedings. Berlin ; Heidelberg ; New York, NY: Springer. S. 152–165. (= Lecture Notes in Computer Science 6107).

Gurulingappa, Harsha et al. (2009): Patent Retrieval in Chemistry based on semantically tagged Named Entities. In: Eighteenth Text REtrieval Conference, TREC 2009. Proceedings.

Klinger, Roman/Friedrich, Christoph M. (2009a): Feature Subset Selection in Conditional Random Fields for Named Entity Recognition. In: Proceedings of the International Conference RANLP-2009. S. 185–191.

Klinger, Roman/Friedrich, Christoph M. (2009b): User’s Choice of Precision and Recall in Named Entity Recognition. In: Proceedings of the International Conference RANLP-2009. Borovets, Bulgaria: Association for Computational Linguistics. S. 192–196.

Kolarik, Corinna/Klinger, Roman/Hofmann-Apitius, Martin (2009): Identification of Histone Modifications in Biomedical Text for Supporting Epigenomic Research. In: BMC Bioinformatics. London: BioMed Central. S. 1–11.

Hofmann-Apitius, Martin et al. (2008): Knowledge Environments Representing Molecular Entities for the Virtual Physiological Human. In: Philosophical transactions of the Royal Society 366.

Klinger, Roman et al. (2008): Detection of IUPAC and IUPAC-like Chemical Names. In: Bioinformatics 24, S. i268–i276.

Kolarik, Corinna et al. (2008): Chemical Names: Terminological Resources and Corpora Annotation. S. 51–58.

Smith, Larry et al. (2008): Overview of BioCreative II gene mention recognition. In: Genome biology 9, S. S2.2-S2.18.

Klinger, Roman et al. (2007a): Named Entity Recognition with Combinations of Conditional Random Fields. In: Proceedings of the Second BioCreative Challenge Evaluation Workshop. Madrid, Spain. S. 89–91.

Klinger, Roman et al. (2007b): Identifying Gene Specific Variations in Biomedical Text. In: Journal of bioinformatics and computational biology 5, S. 1277–1296.

Klinger, Roman/Tomanek, Katrin (2007): Classical Probabilistic Models and Conditional Random Fields. Dortmund: Technische Universität Dortmund. Chair of Algorithm Engineering (LS11). S. 1–31.

Klinger, Roman (2006): Automatische Komposition von Musik mit Methoden der Computational Intelligence. Dortmund: Department of Computer Science, University of Dortmund.