Journal Articles
2017(1 publication)
[publication]Alexandre Pinto and Gonçalo Oliveira, H,  and Alves, A. , "Predicting the Relevance of Social Media Posts Based on Linguistic Features and Journalistic Criteria", New Generation Computing,  vol. 35,  pp. 451-472, 2017
[citation][year=2020]Mahmood, A., Khan, H. U., and Ramzan, M. (2020). On modelling for bias-aware sentiment analysis and its impact in Twitter. Journal of Web Engineering, 19(1):1–28.
[citation][year=2020]Camilleri, S., Agius, M. R., and Azzopardi, J. (2020). Analysis of online news coverage on earthquakes through text mining. Frontiers in Earth Science, 8:141.
[citation][year=2020]Jurado, F. (2020). Journalistic transparency using CRFs to identify the reporter of newspaper articles in Spanish. Applied Soft Computing.
[citation][year=2019]Resende, J. S., Martins, R., and Antunes, L. (2019). A survey on using Kolmogorov complexity in cybersecurity. Entropy, 21(12).
[citation][year=2017]Miranda, F. F. (2017). Computing the accuracy of an automatic system for relevance detection in social networks. Master’s thesis, Universidade do Porto.

Conference Articles
2016(1 publication)
[publication]Alexandre Pinto and Gonçalo Oliveira, H,  and Alves, A. , "Comparing the Performance of Different NLP Toolkits in Formal and Social Media Text", in 5th Symposium on Languages, Applications and Technologies (SLATE'16), 2016
[citation][year=2020]Jalal, M., Mays, K. K., Guo, L., and Betke, M. (2020). Performance comparison of crowdworkers and NLP tools onnamed-entity recognition and sentiment analysis of political tweets.
[citation][year=2020]Ilic, A., Licina, A., and Savic, D. (2020). Chatbot development using java tools and libraries. In 2020 24th International Conference on Information Technology (IT), pages 1–4. IEEE.
[citation][year=2020]Moore, J., Cao, M., and Zhao, R. (2020). Detecting and correcting real-word errors in e-commerce search. In SDM Conference 2020 workshop on Data Science for Retail and E-Commerce Workshop.
[citation][year=2020]James, P. E., Kit, M. H., Vaithilingam, C. A., and Wee Chiat, A. T. (2020). An integrated process based natural language processing system. Journal of Computational and Theoretical Nanoscience, 17(4):1842–1846.
[citation][year=2020]Camilleri, S., Agius, M. R., and Azzopardi, J. (2020). Analysis of online news coverage on earthquakes through text mining. Frontiers in Earth Science, 8:141.
[citation][year=2020]Cheng, X., Kong, X., Liao, L., and Li, B. (2020). A combined method for usage of nlp libraries towards analyzing software documents. In International Conference on Advanced Information Systems Engineering, pages 515–529. Springer.
[citation][year=2020]Borrelli, D., Gongora Svartzman, G., and Lipizzi, C. (2020). Unsupervised acquisition of idiomatic units of symbolic natural language: An n-gram frequency-based approach for the chunking of news articles and tweets. Plos one, 15(6):e0234214.
[citation][year=2020]Camilleri, S. (2020). Deriving business value from online data sources using natural language processing techniques. In Natural Language Processing for Global and Local Business, pages 17–39. IGI Global.
[citation][year=2020]Zemnickis, J., Niedrite, L., and Kozmina, N. (2020). A little bird told me: Discovering KPIs from Twitter data. In International Baltic Conference on Databases and Information Systems, volume 1243 of CCIS, pages 161–175. Springer.
[citation][year=2020]Dolatabadi, M., Fadardi, J. S., Kahani, M., and Karshki, H. (2020). Cognitive sequential dependencies in the wild: Sentiment analysis approach. https://psyarxiv.com/4mw8c/.
[citation][year=2020]Beccaluva, E., Chiappetta, A., Mangut, J. C., Molteni, L., Mores, M., Occhiuto, D., and Garzotto, F. (2020). Deception of the “Elephant in the Room”: Invisible auditing multi-party conversations to support caregivers in cognitive behavioral group therapies. In Human-Computer Interaction. Human Values and Quality of Life. HCII 2020, volume 12183 of LNCS, pages 3–32. Springer.
[citation][year=2019]Evans, L., Crockett, K., Owda, M., and Vilas, A. F. (2019). A Methodology for the Resolution of Cashtag Collisions on Twitter – a Natural Language Processing & Data Fusion Approach. Expert Systems with Applications, page (online since March 2019).
[citation][year=2019]Abrami, G., Mehler, A., Lucking, A., Rieb, E., and Helfrich, P. (2019). Textannotator: A flexible framework for semantic annotations. In Proceedings of 15th Joint ACL - ISO Workshop on Interoperable Semantic Annotation, Gothenburg, Sweden. ACL Press.
[citation][year=2019]Veliz, C. M., De Clercq, O., & Hoste, V. (2019, November). Benefits of Data Augmentation for NMT-based Text Normalization of User-Generated Content. In Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019) (pp. 275-285).
[citation][year=2019]Zimmer, M., Al-Yacoub, A., Ferreira, P., and Lohse, N. (2019). Understanding human decision-making during production ramp-up using Natural Language Processing. In Proceedings of 17th IEEE International Conference on Industrial Informatics (INDIN), Helsinki-Espoo, Finland.
[citation][year=2019]Martinez-Rodriguez, J. L., Lopez-Arevalo, I., Rios-Alvarado, A. B., Hernandez, J., and Aldana-Bobadilla, E. (2019). Extraction of RDF statements from text. In Iberoamerican Knowledge Graphs and Semantic Web Conference, volume 1029 of CCIS, pages 87–101. Springer.
[citation][year=2019]Vychegzhanin, S. and Kotelnikov, E. (2019). Comparison of named entity recognition tools applied to news articles. In 2019 Ivannikov Ispras Open Conference (ISPRAS), pages 72–77.
[citation][year=2019]Zahidi, Y., El Younoussi, Y., and Azroumahli, C. (2019). Comparative study of the most useful Arabic-supporting natural language processing and deep learning libraries. In Proceedings of 5th International Conference on Optimization and Applications (ICOA). IEEE.
[citation][year=2019]Canosa, X., Gamallo, P., Varela, X., Taboada, J. A., Taboada, J. A., and Garcia, M. (2019). Uma utilidade para o reconhecimento de topónimos em documentos medievais. Linguamática, 11(1).
[citation][year=2019]Camilleri, S., Azzopardi, J., and Agius, M. R. (2019). Investigating the relationship between earthquakes and online news. In Proceedings of 2019 IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE). IEEE.
[citation][year=2019]Weiying, K., Pham, D. N., Eftekharypour, Y., and Pheng, A. J. (2019). Benchmarking NLP toolkits for enterprise application. In Proceedings of 16th Pacific Rim International Conference on Artificial Intelligence, Part III, volume 11672 of LNCS, pages 289–294, Cuvu, Yanuca Island, Fiji. Springer.
[citation][year=2019]Lamberti, F., Gatteschi, V., Sanna, A., and Cannavò, A. (published online January 2019). A multimodal interface for virtual character animation based on live performance and natural language processing. International Journal of Human–Computer Interaction, pages 1–17.
[citation][year=2019]Yogish, D., Manjunath, T. N., and Hegadi, R. S. (2019). Review on natural language processing trends and techniques using NLTK. In Proceedings of Second International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2018, Solapur, India, December 21–22, 2018, Revised Selected Papers, Part III, volume 1037 of CCIS, pages 589–606. Springer.
[citation][year=2019]Hausl, M., Forster, J., Auch, M., Karrasch, M., and Mandl, P. (2019). An evaluation concept for named entity recognition and keyword apis in social media analysis. In Proceedings of the Second International Workshop on Entrepreneurship in Electronic and Mobile Business, IWEMB 2018, pages 79–96. PubliQation Academic Publishing.
[citation][year=2019]Sánchez, L. E. (2019). Optimización de modelos de características con aplicaciones para la adaptación de composiciones de servicios. PhD thesis, Universidad Nacional del Centro de la Provincia De Buenos Aires.
[citation][year=2019]Gao, S., Qiu, J. X., Alawad, M., Hinkle, J. D., Schaefferkoetter, N., Yoon, H.-J., Christian, B., Fearn, P. A., Penberthy, L., Wu, X.-C., Coyle, L., Tourassi, G., and Ramanathan, A. (2019). Classifying cancer pathology reports with hierarchical self-attention networks. Artificial Intelligence in Medicine, 101.
[citation][year=2019]Schmitt, X., Kubler, S., Robert, J., Papadakis, M., and LeTraon, Y. (2019). A repli- cable comparison study of ner software: Stanfordnlp, nltk, opennlp, spacy, gate. In Proceedings of Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS). IEEE.
[citation][year=2019]Schwenkler, G. and Zheng, H. (2019). The network of firms implied by the news. Technical Report 3320859, Boston University Questrom School of Business.
[citation][year=2019]Silva, N., Ribeiro, D., and Ferreira, L. (2019). Information extraction from unstructured recipe data. In Proceedings of the 2019 5th International Conference on Computer and Technology Applications, ICCTA 2019, pages 165–168, New York, NY, USA. ACM.
[citation][year=2019]O’Leary, D. E. (2019). What phishing e-mails reveal: An exploratory analysis of phishing attempts using text analyzes. Journal of Information Systems, 33(3):285–307.
[citation][year=2018]Silva, N. G. N. (2018). Information extraction from unstructured recipe data. Master’s thesis, Universidade do Porto.
[citation][year=2018]Nazaruka, E., & Osis, J. (2018, March). Determination of Natural Language Processing Tasks and Tools for Topological Functioning Modelling. In ENASE (pp. 501-512).
[citation][year=2018]Fragkou, P. (2018). Combining information extraction and text segmentation methods in greek texts. Artificial Intelligence Research, 7(1).
[citation][year=2018]Neumer, T. (2018). Efficient natural language processing for automated recruiting on the example of a software engineering talent-pool. Master’s thesis, Technische Universitat Munchen.
[citation][year=2018]Gudivada, V. N., & Arbabifard, K. (2018). Open-Source Libraries, Application Frameworks, and Workflow Systems for NLP. Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, 38, 31.
[citation][year=2018]Suryawati, E., Munandar, D., Riswantini, D., Abka, A. F., and Arisal, A. (2018). Pos-tagging for informal language (study in indonesian tweets). Journal of Physics: Conference Series, 971.
[citation][year=2018]Rudniy, A. (2018). De-identification of laboratory reports in stem. The Journal of Writing Analytics, 2:176–202.
[citation][year=2017]Baumer, F. S. (2017). Indikatorbasierte Erkennung und Kompensation von ungenauen und unvollstandig beschriebenen Softwareanforderungen. PhD thesis, Universitat Paderborn.
[citation][year=2017]da Gama Batista, F. D. (2017). Using named entity recognition for relevance detection in social network messages. Master’s thesis, Universidade do Porto.
[citation][year=2017]Fragkou, P. (2017). Applying named entity recognition and co-reference resolution for seg- menting english texts. Progress in Artificial Intelligence. (online on May 2017)
[citation][year=2017]Batista,F. and Figueira, A. (2017).The complementary nature of different NLP toolkits for named entity recognition in social media. In Progress in Artificial Intelligence - Proceedings of 18th Portuguese Conference on Artificial Intelligence, Porto, Portugal, September 5-8, 2017, volume 10423 of LNCS, pages 803–814. Springer.

MSc Theses
2016(1 publication)
[publication]Alexandre Pinto , "Classification of Social Media Posts according to their Relevance", 2016