Recherche - Symanto

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Forschungsprojekte

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AM PULS DER FORSCHUNG

Unsere Technologie basiert auf wissenschaftlicher Forschung von Experten aus einer Vielzahl von Marktsektoren, darunter Psychologie, KI, NLP und Engineering.

Psychische Gesundheit

Basile, A., Chinea-Rios, M., Uban, A. S., Müller, T., Rössler, L., Yenikent, S., Chulví, B., Rosso, P., & Franco-Salvador, M. (2021). UPV-Symanto at eRisk 2021: Mental Health Author Profiling for Early Risk Prediction on the Internet. In CLEF 2021.
Cohrdes, C., Yenikent, S., Wu, J., Ghanem, B., Franco-Salvador, M., & Vogelgesang, F. (2021). Indications of Depressive Symptoms During the COVID-19 Pandemic in Germany: Comparison of National Survey and Twitter Data. In JMIR Mental Health.

Štajner, S., Yenikent, S., & Franco-Salvador, M. (2021). Five Psycholinguistic Characteristics for Better Interaction with Users. In BESC 2021.
Štajner, S., Yenikent, S., Ghanem, B., & Franco-Salvador, M. (2021). What Motivates You? Benchmarking Automatic Detection of Basic Needs from Short Posts. In ACL-IJNLP 2021.
Štajner, S., & Yenikent, S. (2021). Why Is MBTI Personality Detection from Texts a Difficult Task?. In EACL 2021.
Štajner, S., & Yenikent, S. (2020). A Survey of Automatic Personality Detection from Texts. In COLING 2021.

Psychologisches Profiling

Analyse von Gefühlen, Emotionen und sozialen Medien

Analyse von Stimmungen, Emotionen und Sozialen Medien

Štajner, S. (2021). Exploring Reliability of Gold Labels for Emotion Detection in Twitter. In RANLP 2021.
Ghanem, B., Rosso, P., & Rangel, F. (2020). An Emotional Analysis of False Information in Social Media and News Articles. In ACM Transactions on Internet Technology (TOIT), 20(2), 1-18.
Chinea-Rios, M., Franco-Salvador, M., & Benajiba, Y. (2020). Aspect on: an interactive solution for post-editing the aspect extraction based on online learning. In LREC 2020.
Basile, A., Franco-Salvador, M., Pawar, N., Štajner, S., Rios, M. C., & Benajiba, Y. (2019). Symanto Research at SemEval-2019 task 3: combined neural models for emotion classification in human-chatbot conversations. In SemEval 2019.
Jiang, L., Biran, O., Tiwari, M., Weng, Z., & Benajiba, Y. (2019). End-to-end product taxonomy extension from text reviews. In ICSC 2019.
Giménez-Pérez, R. M., Franco-Salvador, M., & Rosso, P. (2018). String kernels for polarity classification: a study across different languages. In NLDB 2018.
Giménez-Pérez, R. M., Franco-Salvador, M., & Rosso, P. (2018). Single and Cross-domain Polarity Classification using String Kernels. In EACL 2017.

Bevendorff, J., Borrego-Obrador, I., Chinea-Ríos, M., Franco-Salvador, M., Fröbe, M., Heini, A., Kredens, K., Mayerl, M., Pęzik, P., Potthast, M., Rangel, F., Rosso, P., Stamatatos, E., Stein, B., Wiegmann, M., Wolska, M., & Zangerle, E. (2023). Overview of PAN 2023: Authorship Verification, Multi-Author Writing Style Analysis, Profiling Cryptocurrency Influencers, and Trigger Detection. In CLEF 2023.
Chinea-Rios, M., Borrego-Obrador, I., Franco-Salvador, M., Rangel, F., & Rosso, P. (2023). Profiling Cryptocurrency Influencer mit Few-shot Learning. In CLEF 2023.
Bevendorff, J., Chinea-Ríos, M., Franco-Salvador, M., Heini, A., K̈orner, E., Kredens, K., Mayerl, M., Pezik, P., Potthast, M., Rangel, F., Rosso, P. Stamatatos, E., Stein, B., Wiegmann, M., Wolska, M., und Zangerle, E. (2023). Overview of PAN 2023: Authorship Verification, Multi-Author Writing Style Analysis, Profiling Cryptocurrency Influencers, and Trigger Detection. In ECIR 2023.
Chinea-Ríos, M., Müller, T., De La Peña, G., Rangel, F., & Franco-Salvador, M. (2022). Zero and Few-shot Learning for Author Profiling. In NLDB 2022.
Rosso, P., Rangel, F. (2020). Author Profiling Tracks at FIRE. In SN Computer Science 2020.
Ghanem, B.,Giachanou, A., Kestemont, M., Manjavacas, E., Potthast, M., Rangel, F., Rosso, P., Specht, G., Stamatatos, E., Stein, B., Wiegmann, M., Zangerle, E. (2020). Shared Tasks on Authorship Analysis at PAN 2020. In ECIR 2020.
Franco-Salvador, M., Kondrak, G., & Rosso, P. (2017). Bridging the native language and language variety identification tasks. In KES 2017.
Franco-Salvador, M., Plotnikova, N., Pawar, N., & Benajiba, Y. (2017). Subword-based Deep Averaging Networks for Author Profiling in Social Media. In CLEF 2017.

Autorenprofilierung

Autoren - Profiling

Hassrede-Erkennung

Hassreden-Erkennung

De La Peña, G., & Rosso, P. (2022). Unsupervised Embeddings with Graph Auto-Encoders for Multi-domain and Multilingual Hate Speech Detection. In LREC 2022.
De La Peña, G., & Rosso, P. (2022). Convolutional Graph Neural Networks for Hate Speech Detection in Data-Poor Settings. In NLDB 2022.
Rangel, F., De La Peña, G., Chulvi, B., Fersini, E., & Rosso, P. (2021). Profiling hate speech spreaders on twitter task at PAN 2021. In CLEF 2021.
Bevendorff, J., Chulvi, B., De La Peña, G., Kestemont, M., Manjavacas, E., Markov, I., Mayerl, M., Potthast, M., Rangel, F., Rosso, P., Stamatatos, E., Stein, B., Wiegmann, M., Zangerle, E. (2021). Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection. In ECIR 2021.
Bevendorff, J., Chulvi, B., De La Peña, G., Kestemont, M., Manjavacas, E., Markov, I., Mayerl, M., Potthast, M., Rangel, F., Rosso, P., Stamatatos, E., Stein, B., Wiegmann, M., Zangerle, E. (2021). Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection. (extended version). In CLEF 2021.

Basile, A. Franco-Salvador, M., & Rosso, P. (2023). Zero-Shot Datenkarten. In Findings of EMNLP 2023.
Basile, A., Franco-Salvador, M., & Rosso, P.(2022). Unsupervised Ranking and Aggregation of Label Descriptions for Zero-Shot Classifiers. In NLDB 2022.
Müller, T., Pérez-Torró, G., Basile, A., & Franco-Salvador, M. (2022). Active Few-Shot Learning with FASL. In NLDB 2022.
Müller, T., Pérez-Torró, G., & Franco-Salvador, M. (2022). Few-Shot Learning with Siamese Networks and Label Tuning. In ACL 2022.
Basile, A., Pérez-Torró, G., & Franco-Salvador, M. (2021). Probabilistic Ensembles of Zero- and Few-Shot Learning Models for Emotion Classification. In RANLP 2021.
Outahajala, M., Benajiba, Y., Rosso, P., & Zenkouar, L. (2015). Using confidence and informativeness criteria to improve POS-tagging in amazigh. In Journal of Intelligent & Fuzzy Systems.

Low-Resource-NLP

Textliche Ähnlichkeit

Textähnlichkeit

Benajiba, Y., Sun, J., Zhang, Y., Jiang, L., Weng, Z., & Biran, O. (2019). Siamese networks for semantic pattern similarity. In ICSC 2019.
Glavaš, G., Franco-Salvador, M., Ponzetto, S. P., & Rosso, P. (2018). A resource-light method for cross-lingual semantic textual similarity. In Knowledge-based Systems 2018.
Álvarez-Carmona, M. A., Franco-Salvador, M., Villatoro-Tello, E., Montes-y-Gómez, M., Rosso, P., & Villaseñor-Pineda, L. (2018). Semantically-informed distance and similarity measures for paraphrase plagiarism identification. In Journal of Intelligent & Fuzzy Systems.

Štajner, S., Franco-Salvador, M., Rosso, P., & Ponzetto, S. P. (2018). CATS: A tool for customized alignment of text simplification corpora. LREC 2018.
Štajner, S., Franco-Salvador, M., Ponzetto, S. P., Rosso, P., & Stuckenschmidt, H. (2017). Sentence alignment methods for improving text simplification systems. In ACL 2017.

Vereinfachung des Textes

Textvereinfachung

Erkennung von Fake News

Fake-News-Erkennung

Ghanem, B., Ponzetto, S. P., Rosso, P., & Rangel, F. (2021). Fakeflow: Fake news detection by modeling the flow of affective information. In EACL 2021.
Rangel, F., Giachanou, A., Ghanem, B., Rosso, P. (2020). Overview of the 8th Author Profiling Task at PAN 2020: Profiling Fake News Spreaders on Twitter. In CLEF 2020.
Bevendorff, J., Ghanem, B., Giachanou, A., Kestemont, M., Manjavacas, E., Markov, I., Mayerl, M., Potthast, M., Rangel, F., Rosso, P., Specht, G., Stamatatos, E., Stein, B., Wiegmann, M., Zangerle, E. (2020). Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection. In CLEF 2020.

Krichene, S., Müller, T., & Eisenschlos, J. M. (2021). DoT: An efficient Double Transformer for NLP tasks with tables. In Findings of ACL 2021.
Eisenschlos, J. M., Maharshi, G., Müller, T., & Cohen, W. C. (2021). MATE: Multi-view Attention for Table Transformer Efficiency. In EMNLP 2021.

Frage beantworten

Fragen Beantwortung

Ereignis-Extraktion

Event Extraction

Caselli, T., Mutlu, O., Basile & A., Hürriyetoğlu A. (2021). PROTEST-ER: Retraining BERT for Protest Event Extraction. In CASE 2021.
Basile, A., & Caselli, T. (2020). Protest Event Detection: When Task-Specific Models Outperform an Event-Driven Method. In CLEF 2020.

Sarvazyan, A. M., González, J. A., Franco-Salvador, M., Rangel, F., Chulvi, B., & Rosso, P. (2023). Überblick über AuTexTification auf der IberLEF 2023: Erkennung und Zuordnung von maschinell erzeugtem Text in mehreren Domänen. In Sociedad Española de Procesamiento del Languaje Natural.
Sarvazyan, A. M., González, J. A., Rosso, P., & Franco-Salvador, M. (2023). Überwachte maschinengenerierte Textdetektoren: Familie und Maßstab spielen eine Rolle. In CLEF 2023.

Maschinell erzeugter Text

MASCHINENGENERIERTER TEXT

ANDERE

Whitehouse, E., Gerard, W., Klimovich, Y., & Franco-Salvador, M. (2022). Programming by Example and Text-to-Code Translation for Conversational Code Generation. In arXiv preprint, 2022.

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Entdecken Sie die Wissenschaft hinter Natural Language Processing mit unserer bahnbrechenden NLP-Forschung

Forschungsprojekte

Forschungspapiere

AM PULS DER FORSCHUNG

Psychische Gesundheit

Psychische Gesundheit

Psychologisches Profiling

Psychologisches Profiling

Analyse von Gefühlen, Emotionen und sozialen Medien

Analyse von Stimmungen, Emotionen und Sozialen Medien

Autorenprofilierung

Autoren - Profiling

Hassrede-Erkennung

Hassreden-Erkennung

Low-Resource-NLP

Low-Resource-NLP

Textliche Ähnlichkeit

Textähnlichkeit

Vereinfachung des Textes

Textvereinfachung

Erkennung von Fake News

Fake-News-Erkennung

Frage beantworten

Fragen Beantwortung

Ereignis-Extraktion

Event Extraction

Maschinell erzeugter Text

MASCHINENGENERIERTER TEXT

ANDERE

ANDERE

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