2024
Grotenhuis, Z., Mosteiro Romero, P., & Leeuwenberg, A. J. M. (Accepted/In press). Modest performance of text mining to extract health outcomes may be almost sufficient for high-quality prognostic model development. Computers in Biology and Medicine, 170. https://doi.org/10.1016/j.compbiomed.2024.108014
2023
Ruffo, G., Semeraro, A., Giachanou, A., & Rosso, P. (2023). Studying fake news spreading, polarisation dynamics, and manipulation by bots: A tale of networks and language. Computer science review, 47, 100531.
Mohammadi, H., Giachanou, A., & Bagheri, A. (2023). Towards robust online sexism detection: a multi-model approach with BERT, XLM-RoBERTa, and DistilBERT for EXIST 2023 Tasks. Working Notes of CLEF.
Pavliuc, A., George, A., Spezzano, F., Giachanou, A., Spaiser, V., & Bright, J. (2023). Multidisciplinary Approaches to Mis-and Disinformation Studies. Social Media+ Society, 9(1), 20563051221150405.
Bagheri, A., Giachanou, A., Mosteiro Romero, P., & Verberne, S. (2023). Natural Language Processing and Text Mining (Turning Unstructured Data into Structured). In F. Asselbergs, S. Denaxas, D. Oberski, & J. Moore (Eds.), Clinical Applications of Artificial Intelligence in Real-World Data (1 ed., pp. 69-93). Springer. https://doi.org/10.1007/978-3-031-36678-9_5
Ito, T., Fang, Q., Mosteiro Romero, P., Gatt, A., & van Deemter, K. (2023). Challenges in Reproducing Human Evaluation Results for Role-Oriented Dialogue Summarization. In The 3rd Workshop on Human Evaluation of NLP Systems (HumEval’23) ACL Anthology. https://aclanthology.org/2023.humeval-1.9
van Buchem, M. M., ‘t Hart, H., Mosteiro Romero, P., Kant, I. M. J., & Bauer, M. P. (2023). Diagnosis Classification in the Emergency Room Using Natural Language Processing. In Caring is Sharing – Exploiting the Value in Data for Health and Innovation (pp. 815 – 816). (Studies in Health Technology and Informatics; Vol. 302). IOS Press. https://doi.org/10.3233/SHTI230273
Anya Belz, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose M. Alonso-Moral, Mohammad Arvan, Anouck Braggaar, Mark Cieliebak, Elizabeth Clark, Kees van Deemter, Tanvi Dinkar, Ondřej Dušek, Steffen Eger, Qixiang Fang, Mingqi Gao, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Mosteiro Romero, P., et al.. 2023. Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP. In The Fourth Workshop on Insights from Negative Results in NLP, pages 1–10, Dubrovnik, Croatia. Association for Computational Linguistics. https://aclanthology.org/2023.insights-1.1
Fang, Q., Zhou, Z., Barbieri, F., Liu, Y., Neves, L., Nguyen, D., … & Dotsch, R. (2023). Designing and Evaluating General-Purpose User Representations Based on Behavioral Logs from a Measurement Process Perspective: A Case Study with Snapchat. arXiv preprint arXiv:2312.12111.
Fang, Q., Giachanou, A., Bagheri, A., Boeschoten, L., van Kesteren, E. J., Kamalabad, M. S., & Oberski, D. L. (2022). On Text-based Personality Computing: Challenges and Future Directions. arXiv preprint arXiv:2212.06711.
Fang, C., Fang, Q., & Nguyen, D. (2023). Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions. arXiv preprint arXiv:2302.13925.
Qi Q, Hessen DJ, Deoskar T, van der Heijden PGM. A comparison of latent semantic analysis and correspondence analysis of document-term matrices. Natural Language Engineering. Published online 2023:1-31. doi:10.1017/S1351324923000244
Qi, Q., Hessen, D.J. & van der Heijden, P.G.M. Improving information retrieval through correspondence analysis instead of latent semantic analysis. J Intell Inf Syst (2023). https://doi.org/10.1007/s10844-023-00815-y
2022
Afsharizadeh, M., Ebrahimpour-Komleh, H., Bagheri, A., & Chrupała, G. (2022). A survey on multi-document summarization and domain-oriented approaches. Journal of Information Systems and Telecommunication (JIST), 1(37), 68.
de Jong, D., & Bagheri, A. (2022). The case of imperfect negation cues: A two-step approach for automatic negation scope resolution. International Conference on Applications of Natural Language to Information Systems, 413–424.
Giachanou, A., Ghanem, B., Ríssola, E. A., Rosso, P., Crestani, F., & Oberski, D. (2022). The impact of psycholinguistic patterns in discriminating between fake news spreaders and fact checkers. Data & Knowledge Engineering, 138, 101960.
Giachanou, A., Zhang, X., Barrón-Cedeño, A., Koltsova, O., & Rosso, P. (2022). Online information disorder: Fake news, bots and trolls (pp. 1–5). Springer International Publishing.
Keuren, P., Ponsen, M., & Bagheri, A. (2022). WordGraph2Vec: Combining domain knowledge with text embeddings. Joint International Scientific Conferences on AI and Machine Learning.
Teijema, J., Hofstee, L., Brouwer, M., de Bruin, J., Ferdinands, G., de Boer, J., Siso, P. V., van den Brand, S., Bockting, C., van de Schoot, R., & others. (2022). Active learning-based Systematic reviewing using switching classification models: The case of the onset, maintenance, and relapse of depressive disorders.
van Driel, I. I., Giachanou, A., Pouwels, J. L., Boeschoten, L., Beyens, I., & Valkenburg, P. M. (2022). Promises and pitfalls of social media data donations. Communication Methods and Measures, 1–17.
Zhang, G., Giachanou, A., & Rosso, P. (2022). SceneFND: Multimodal fake news detection by modelling scene context information. Journal of Information Science, 01655515221087683.
Borger, T., Mosteiro Romero, P., Kaya, H., Rijcken, E., Salah, A., Scheepers, F., & Spruit, M. (2022). Federated learning for violence incident prediction in a simulated cross-institutional psychiatric setting. Expert Systems with Applications, 199, 1-9. Article 116720. https://doi.org/10.1016/j.eswa.2022.116720
Rijcken, E., Kaymak, U., Scheepers, F. E., Mosteiro Romero, P., Zervanou, K., & Spruit, M. (2022). Topic Modeling for Interpretable Text Classification From EHRs. Frontiers in Big Data, 5, 1-11. Article 846930. https://doi.org/10.3389/fdata.2022.846930
Rijcken, E., Zervanou, K., Spruit, M., Mosteiro Romero, P., Scheepers, F. E., & Kaymak, U. (2022). Exploring Embedding Spaces for more Coherent Topic Modeling in Electronic Health Records. In IEEE International Conference on Systems, Man, and Cybernetics (pp. 2669-2674). IEEE. https://doi.org/10.1109/SMC53654.2022.9945594
Sarhan, I., Mosteiro Romero, P., & Spruit, M. (2022). UU-Tax at SemEval-2022 Task 3: Improving the generalizability of language models for taxonomy classification through data augmentation. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) (pp. 271-281). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.35
Mosteiro Romero, P., Kuiper, J., Masthoff, J., Scheepers, F. E., & Spruit, M. (2022). Bias Discovery in Machine Learning Models for Mental Health. Information, 13(5), 1-15. Article 237. https://doi.org/10.3390/info13050237
Fang, Q., Nguyen, D., & Oberski, D. L. (2022). Evaluating the construct validity of text embeddings with application to survey questions. EPJ Data Science, 11(1), 39.
Fang, Q., Giachanou, A., & Bagheri, A. (2022). Modelling Stance Detection as Textual Entailment Recognition and Leveraging Measurement Knowledge from Social Sciences. arXiv preprint arXiv:2212.06543.
2021
Bagheri, A. (2021). Text mining in healthcare: Bringing structure to electronic health records. Utrecht University.
Bagheri, A., Groenhof, T. K. J., Asselbergs, F. W., Haitjema, S., Bots, M. L., Veldhuis, W. B., De Jong, P. A., & Oberski, D. L. (2021). Automatic prediction of recurrence of major cardiovascular events: A text mining study using chest X-ray reports. Journal of Healthcare Engineering, 2021.
Boeschoten, L., van Kesteren, E.-J., Bagheri, A., & Oberski, D. L. (2021). Achieving fair inference using error-prone outcomes.
Bright, J., Giachanou, A., Spaiser, V., Spezzano, F., George, A., & Pavliuc, A. (2021). Disinformation in open online media. Springer International Publishing.
Felix, S. E., Bagheri, A., Ramjankhan, F. R., Spruit, M. R., Oberski, D., De Jonge, N., Van Laake, L. W., Suyker, W. J., & Asselbergs, F. W. (2021). A data mining-based cross-industry process for predicting major bleeding in mechanical circulatory support. European Heart Journal-Digital Health, 2(4), 635–642.
Giachanou, A., Ghanem, B., & Rosso, P. (2021). Detection of conspiracy propagators using psycho-linguistic characteristics. Journal of Information Science, 0165551520985486.
Giachanou, A., Rosso, P., & Crestani, F. (2021). The impact of emotional signals on credibility assessment. Journal of the Association for Information Science and Technology, 72(9), 1117–1132.
Nguyen, H. T. T. (2021). Words Matter? Gender Disparities in Speeches, Evaluation and Competitive Performance (No. 789) [Tinbergen Instituut Research Series]. Erasmus University Rotterdam.
Nguyen, H., Vente, R., Lupea, D., Levitan, S. I., & Hirschberg, J. (2021). Acoustic-prosodic, lexical and demographic cues to persuasiveness in competitive debate speeches. Interspeech, 1034–1038.
Rosso, P., Ghanem, B., & Giachanou, A. (2021). On the impact of emotions on the detection of false information. 2021 International Symposium on Electrical, Electronics and Information Engineering, 277–282.
Ruffo, G., Semeraro, A., Giachanou, A., & Rosso, P. (2021). Surveying the research on fake news in social media: A tale of networks and language. ArXiv Preprint ArXiv:2109.07909.
Sammani, A., Bagheri, A., van der Heijden, P. G., Te Riele, A. S., Baas, A. F., Oosters, C., Oberski, D., & Asselbergs, F. W. (2021). Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks. NPJ Digital Medicine, 4(1), 1–10.
Van Driel, I., Giachanou, A., Pouwels, J. L., Boeschoten, L., Beyens, I., Valkenburg, P. M., & others. (2021). Promises and pitfalls of Instagram data donations.
Yang, Z., Bagheri, A., & van der Heijden, P. (2021). Neural networks for latent budget analysis of compositional data. ArXiv Preprint ArXiv:2109.04875.
Rijcken, E., Scheepers, F. E., Mosteiro Romero, P., Zervanou, K., Spruit, M., & Kaymak, U. (2021). A Comparative Study of Fuzzy Topic Models and LDA in terms of Interpretability. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (SSCI 2021) (pp. 1-8). IEEE. https://doi.org/10.1109/SSCI50451.2021.9660139
Mosteiro Romero, P., Rijcken, E., Zervanou, K., Kaymak, U., Scheepers, F. E., & Spruit, M. (2021). Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes. Journal of Artificial Intelligence for Medical Sciences, 2( 1-2), 44-54. https://doi.org/10.2991/jaims.d.210225.001
Du, Y., Fang, Q., & Nguyen, D. (2021). Assessing the reliability of word embedding gender bias measures. arXiv preprint arXiv:2109.04732.
Fang, Q., Burger, J., Meijers, R., & van Berkel, K. (2021). The Role of Time, Weather and Google Trends in Understanding and Predicting Web Survey Response. Survey Research Methods, 15(1), 1–25. https://doi.org/10.18148/srm/2021.v15i1.7633
Arts, I., Fang, Q., van de Schoot, R., & Meitinger, K. (2021). Approximate measurement invariance of willingness to sacrifice for the environment across 30 countries: The importance of prior distributions and their visualization. Frontiers in Psychology, 12, 624032.
2020
Afsharizadeh, M., EBRAHIMPOUR, K. H., & Bagheri, A. (2020). Automatic text summarization of COVID-19 research articles using recurrent neural networks and coreference resolution.
Bagheri, A., Groenhof, T. K. J., Veldhuis, W. B., de Jong, P. A., Asselbergs, F. W., & Oberski, D. L. (2020). Multimodal learning for cardiovascular risk prediction using EHR data. ArXiv Preprint ArXiv:2008.11979.
Bagheri, A., Sammani, A., van der Heijden, P. G., Asselbergs, F. W., & Oberski, D. L. (2020a). Automatic ICD-10 classification of diseases from dutch discharge letters. 13th International Joint Conference on Biomedical Engineering Systems and Technologies – BIOSTEC2020, 281–289.
Bagheri, A., Sammani, A., van der Heijden, P. G., Asselbergs, F. W., & Oberski, D. L. (2020b). ETM: Enrichment by topic modeling for automated clinical sentence classification to detect patients’ disease history. Journal of Intelligent Information Systems, 55(2), 329–349.
Bevendorff, J., Ghanem, B., Giachanou, A., Kestemont, M., Manjavacas, E., Markov, I., Mayerl, M., Potthast, M., Rangel, F., Rosso, P., & others. (2020). Overview of PAN 2020: Authorship verification, celebrity profiling, profiling fake news spreaders on Twitter, and style change detection. International Conference of the Cross-Language Evaluation Forum for European Languages, 372–383.
Bevendorff, J., Ghanem, B., Giachanou, A., Kestemont, M., Manjavacas, E., Potthast, M., Rangel, F., Rosso, P., Specht, G., Stamatatos, E., & others. (2020). Shared tasks on authorship analysis at pan 2020. European Conference on Information Retrieval, 508–516.
Boeschoten, L., van Kesteren, E.-J., Bagheri, A., & Oberski, D. L. (2020). Fair inference on error-prone outcomes. ArXiv Preprint ArXiv:2003.07621.
De la Peña Sarracén, G. L., Rosso, P., & Giachanou, A. (2020). PRHLT-UPV at SemEval-2020 task 8: Study of multimodal techniques for memes analysis. Proceedings of the Fourteenth Workshop on Semantic Evaluation, 908–915.
Ferdinands, G., Schram, R., Bruin, J. de, Bagheri, A., Oberski, D. L., Tummers, L., Schoot, R. van de, & others. (2020). Active learning for screening prioritization in systematic reviews-A simulation study.
Foroozande, E., Bagheri, A., & others. (2020). Line bisection test software to evaluate the visual-spatial functions in schizophrenic patients.
Giachanou, A., Ríssola, E. A., Ghanem, B., Crestani, F., & Rosso, P. (2020). The role of personality and linguistic patterns in discriminating between fake news spreaders and fact checkers. International Conference on Applications of Natural Language to Information Systems, 181–192.
Giachanou, A., & Rosso, P. (2020). The battle against online harmful information: The cases of fake news and hate speech. Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 3503–3504.
Giachanou, A., Zhang, G., & Rosso, P. (2020a). Multimodal fake news detection with textual, visual and semantic information. International Conference on Text, Speech, and Dialogue, 30–38.
Giachanou, A., Zhang, G., & Rosso, P. (2020b). Multimodal multi-image fake news detection. 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 647–654.
Rangel, F., Giachanou, A., Ghanem, B. H. H., & Rosso, P. (2020). Overview of the 8th author profiling task at pan 2020: Profiling fake news spreaders on twitter. CEUR Workshop Proceedings, 2696, 1–18.
Rangel, F., Rosso, P., Ghanem, B., & Giachanou, A. (2020). Profiling fake news spreaders on twitter. PAN at CLEF.
van Berkel, N., Papachristos, E., Giachanou, A., Hosio, S., & Skov, M. B. (2020). A systematic assessment of national artificial intelligence policies: Perspectives from the Nordics and beyond. Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society, 1–12.
van de Leur, R. R., Boonstra, M. J., Bagheri, A., Roudijk, R. W., Sammani, A., Taha, K., Doevendans, P. A., van der Harst, P., van Dam, P. M., Hassink, R. J., & others. (2020). Big data and artificial intelligence: Opportunities and threats in electrophysiology. Arrhythmia & Electrophysiology Review, 9(3), 146.
Mosteiro Romero, P. J., Rijcken, E., Zervanou, K., Kaymak, U., Scheepers, F., & Spruit, M. (2020). Making sense of violence risk predictions using clinical notes. In Z. Huang, S. Siuly, H. Wang, R. Zhou, & Y. Zhang (Eds.), Health Information Science: 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings (pp. 3-14). (Lecture Notes in Computer Science; Vol. 12435). Springer Cham. https://doi.org/10.1007/978-3-030-61951-0_1
2019
Bagheri, A. (2019). Integrating word status for joint detection of sentiment and aspect in reviews. Journal of Information Science, 45(6), 736–755.
Bagheri, A., Oberski, D., Sammani, A., van der Heijden, P. G., & Asselbergs, F. W. (2019). SALTClass: Classifying clinical short notes using background knowledge from unlabeled data. BioRxiv : The Preprint Server for Biology, 801944.
Ghanem, B., Glavaš, G., Giachanou, A., Ponzetto, S. P., Rosso, P., & Rangel, F. (2019). UPV-UMA at CheckThat! Lab: Verifying Arabic claims using a cross lingual approach. CEUR Workshop Proceedings, 2380, 1–10.
Giachanou, A., & Ghanem, B. (2019). Bot and gender detection using textual and stylistic information. Pan. Studi Dell’istituto Di Filologia Latina, 16(5).
Giachanou, A., Gonzalo, J., & Crestani, F. (2019). Propagating sentiment signals for estimating reputation polarity. Information Processing & Management, 56(6), 102079.
Giachanou, A., Rosso, P., & Crestani, F. (2019). Leveraging emotional signals for credibility detection. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 877–880.
Métais, E., Meziane, F., Sararee, M., Sugumaran, V., & Vadera, S. (2019). Natural language processing and information systems. Springer International Publishing.
Sammani, A., Jansen, M., Linschoten, M., Bagheri, A., de Jonge, N., Kirkels, H., van Laake, L., Vink, A., van Tintelen, J., Dooijes, D., & others. (2019). UNRAVEL: big data analytics research data platform to improve care of patients with cardiomyopathies using routine electronic health records and standardised biobanking. Netherlands Heart Journal, 27(9), 426–434.
Sedighi, Z., Ebrahimpoor-Komleh, H., Bagheri, A., & Kosseim, L. (2019). Opinion spam detection with attention-based neural networks. The Thirty-Second International Flairs Conference.
2018
Afsharizadeh, M., Ebrahimpour-Komleh, H., & Bagheri, A. (2018). Query-oriented text summarization using sentence extraction technique. 2018 4th International Conference on Web Research (ICWR).
Asgarnezhad, R., Monadjemi, S. A., Soltanaghaei, M., & Bagheri, A. (2018). SFT: A model for sentiment classification using supervised methods on twitter. Journal of Theoretical & Applied Information Technology, 96(8).
Bagheri, A., & Nadi, S. (2018). Sentiment miner: A novel unsupervised framework for aspect detection from customer reviews.
Fuhr, N., Giachanou, A., Grefenstette, G., Gurevych, I., Hanselowski, A., Jarvelin, K., Jones, R., Liu, Y., Mothe, J., Nejdl, W., & others. (2018). An information nutritional label for online documents. ACM SIGIR Forum, 51, Article 3.
Giachanou, A. (2018). Tracking public opinion on social media. Università della Svizzera italiana.
Giachanou, A., Rosso, P., Mele, I., & Crestani, F. (2018a). Early commenting features for emotional reactions prediction. International Symposium on String Processing and Information Retrieval, 168–182.
Giachanou, A., Rosso, P., Mele, I., & Crestani, F. (2018b). Emotional influence prediction of news posts. Twelfth International AAAI Conference on Web and Social Media.
Giachanou, A., Rosso, P., Mele, I., & Crestani, F. (2018c). Emotional reactions prediction of news posts. IIR.
Lomi, A., Giachanou, A., Crestani, F., & Angelopoulos, S. (2018). Table for two: Explaining variations in the evaluation of authenticity by restaurant critics.
Ríssola, E., Giachanou, A., & Crestani, F. (2018). USI-IR at IEST 2018: Sequence modeling and pseudo-relevance feedback for implicit emotion detection. Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 231–234.
2017
Dewi Varathan, K., Giachanou, A., & Crestani, F. (2017). Comparative opinion mining: A review. ArXiv E-Prints, arXiv-1712.
Giachanou, A., Gonzalo, J., Mele, I., & Crestani, F. (2017). Sentiment propagation for predicting reputation polarity. European Conference on Information Retrieval, 226–238.
Giachanou, A., Mele, I., & Crestani, F. (2017a). A collection for detecting triggers of sentiment spikes. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 1249–1252.
Giachanou, A., Mele, I., & Crestani, F. (2017b). USI participation at SMERP 2017 text retrieval task. Proceedings of Exploitation of Social Media for Emergency Relief and Preparedness (SMERP) Workshop (Data Challenge Track).
Giachanou, A., Mele, I., & Crestani, F. (2017c). USI participation at SMERP 2017 text summarization task. Proceedings of Exploitation of Social Media for Emergency Relief and Preparedness (SMERP) Workshop (Data Challenge Track).
Giachanou, A., Rangel, F., Crestani, F., & Rosso, P. (2017). Emerging sentiment language model for emotion detection. Italian Conference on Computational Linguistics.
Jabalameli, A., Mehdi, V. S., & Bagheri, A. (2017). A centralized crawler for web community detection. 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI-2017), 4.
Madjidi, E., & Bagheri, A. (2017). Providing a method for classifying users’ comments using machine learning and voting algorithm. 1st International Conference on Modern Technologies in Sciences, 1.
Maleki, M. J., & Bagheri, A. (2017). Multi-word effect on analysis of online reviews sentiments. 3rd International Conference on Pattern Recognition & Image Analysis, Shahrekord, Iran.
Sedighi, Z., Ebrahimpour-Komleh, H., & Bagheri, A. (2017). RLOSD: Representation learning based on OpinionSpam detection. 11th International Conference on Computer Science and Information Technologies, 1–7.
Varathan, K. D., Giachanou, A., & Crestani, F. (2017). Comparative opinion mining: A review. Journal of the Association for Information Science and Technology, 68(4), 811–829.
2016
Giachanou, A., & Crestani, F. (2016a). Like it or not: A survey of twitter sentiment analysis methods. ACM Computing Surveys (CSUR), 49(2), 1–41.
Giachanou, A., & Crestani, F. (2016b). Opinion retrieval in Twitter: Is proximity effective? ACM Symposium on Applied Computing.
Giachanou, A., & Crestani, F. (2016c). Opinion retrieval in Twitter using stylistic variations. ACM Symposium on Applied Computing.
Giachanou, A., & Crestani, F. (2016d). Tracking sentiment by time series analysis. Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, 1037–1040.
Giachanou, A., Harvey, M., & Crestani, F. (2016). Topic-specific stylistic variations for opinion retrieval on twitter. European Conference on Information Retrieval, 466–478.
Giachanou, A., Mele, I., & Crestani, F. (2016). Explaining sentiment spikes in twitter. 25th ACM International on Conference on Information and Knowledge Management.
Lomi, A., Giachanou, A., Crestani, F., & Angelopoulos, S. (2016). Table for two: The effects of relational and categorical organizational identities on restaurants reviews. 36th Sunbelt Conference (INSNA).
Varathan, K. D., Giachanou, A., & Crestani, F. (2016). Temporal analysis of comparative opinion mining. International Conference on Asian Digital Libraries, 311–322.
Varathan, K. D., Giachanou, A., Crestani, F., Belém, F. M., Almeida, J. M., Gonçalves, M. A., Finnemann, N. O., Cai, F., Wang, S., de Rijke, M., & others. (2016). JASIST. Evaluation, 884.
Zaghian, A., & Bagheri, A. (2016). A combined model of clustering and classification methods for preserving privacy in social networks against inference and neighborhood attacks. International Journal of Security and Its Applications, 10(1), 95–110.
2015
Aliannejadi, M., Bahrainian, S. A., Giachanou, A., & Crestani, F. (2015). University of lugano at TREC 2015: Contextual suggestion and temporal summarization tracks. Twenty-Fourth Text REtrieval Conference (TREC 2015).
Giachanou, A., Salampasis, M., & Paltoglou, G. (2015). Multilayer source selection as a tool for supporting patent search and classification. Information Retrieval Journal, 18(6), 559–585.
2014
Bagheri, A., & Saraee, M. (2014). Persian sentiment analyzer: A framework based on a novel feature selection method. International Journal of Artificial Intelligence, ArXiv Preprint ArXiv:1412.8079.
Bagheri, A., Saraee, M., & De Jong, F. (2014). ADM-LDA: An aspect detection model based on topic modelling using the structure of review sentences. Journal of Information Science, 40(5), 621–636.
Bagheri, A., Saraee, M., & Nadi, S. (2014). PSA: a hybrid feature selection approach for Persian text classification. Journal of Computing and Security, 1(4), 261–272.
Giachanou, A., Markov, I., & Crestani, F. (2014). Opinions in federated search: University of lugano at TREC 2014 federated web search track. Twenty-Third Text REtrieval Conference (TREC 2014).
Giachanou, A., & Salampasis, M. (2014). IPC selection using collection selection algorithms. Information Retrieval Facility Conference, 41–52.
Giachanou, A., Salampasis, M., Satratzemi, M., & Samaras, N. (2014). A user-centered evaluation of a web based patent classification tool. MindTheGap@ IConference, 6–11.
Paltoglou, G., & Giachanou, A. (2014). Opinion retrieval: Searching for opinions in social media. In Professional search in the modern world (pp. 193–214). Springer, Cham.
Salampasis, M., Giachanou, A., & Hanbury, A. (2014). An evaluation of an interactive federated patent search system. Information Retrieval Facility Conference, 120–131.
Salampasis, M., Paltoglou, G., & Giachanou, A. (2014). Using social media for continuous monitoring and mining of consumer behaviour. 11(1), 85–96.
2013
Bagheri, A., Saraee, M., & De Jong, F. (2013). Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews. Knowledge-Based Systems, 52, 201–213.
Bagheri, A., Saraee, M., De Jong, F., & others. (2013). Latent Dirichlet Markov allocation for sentiment analysis.
Bagheri, A., Saraee, M., & Jong, F. de. (2013). An unsupervised aspect detection model for sentiment analysis of reviews. International Conference on Application of Natural Language to Information Systems, 140–151.
Giachanou, A., Salampasis, M., & Paltoglou, G. (2013). Multilayer collection selection and search of topically organized patents. In Proceedings of the Integrating IR Technologies for Professional Search (in Conjuction with ECIR 2013).
Giachanou, A., Salampasis, M., Satratzemi, M., & Samaras, N. (2013). Report on the CLEF-IP 2013 experiments: Multilayer collection selection on topically organized patents. CLEF 2013 Conference and Labs of the Evaluation Forum (Online Working Notes/Labs/Workshop).
Saraee, M., & Bagheri, A. (2013). Feature selection methods in Persian sentiment analysis. International Conference on Application of Natural Language to Information Systems, 303–308.
2012
Salampasis, M., Paltoglou, G., & Giachanou, A. (2012). Report on the CLEF-IP 2012 experiments: Search of topically organized patents. CLEF (Online Working Notes/Labs/Workshop).
2011
Salampasis, M., Paltoglou, G., & Giachanou, A. (2011). Using social media for continuous monitoring and mining of consumer behaviour. 5th International Conference on Information and Communication Technologies in Agriculture, Food and Environment.
Bagheri, A., & Giachanou, A. (n.d.). Sentiment analysis.
Sedighi, Z., Ebrahimpour-Komleh, H., Bagheri, A., & Kosseim, L. (n.d.). Opinion spam detection with attention-based LSTM networks.