NLP RESEARCH

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Who's behind this text?

Language: English
Tonality: positive
Emotion: joy
Personality trait: rational

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Who's behind this text?

Language: English
Tonality: positive
Emotion: joy
Personality trait: rational

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BEYOND THE CUTTING EDGE

BEYOND THE CUTTING EDGE

Our technology is based on scientific research by experts in a wide range of market sectors, including psychology, AI, NLP and engineering.

Mental Health

Psychological Profiling

Sentiment, Emotion & Social Media Analysis

Author Profiling

Hate-speech Detection

Low-resource NLP

Textual Similarity

Text Simplification

Fake News Detection

Question Answering

Event Extraction

Mental Health

Mental Health

• 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.

Psychological Profiling

Psychological Profiling

Sentiment, Emotion & Social Media Analysis

Sentiment, Emotion & Social Media Analysis

• 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.

• 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.

Author Profiling

Author Profiling

Hate-speech Detection

Hate-speech Detection

• 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.(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

Low-resource NLP

Textual Similarity

Textual Similarity

• 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.

Text Simplification

Text Simplification

Fake News Detection

Fake News Detection

• 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.

Question Answering

Question Answering

Event Extraction

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.

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