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Rau, M. Röglinger, T. Schoormann, and Daniel Szopinski. “An Update for Taxonomy Designers: Methodological Guidance from Information Systems Research.” <i>Business &#38; Information Systems Engineering</i> 64, no. 4 (2022): 421–39.","mla":"Kundisch, Dennis, et al. “An Update for Taxonomy Designers: Methodological Guidance from Information Systems Research.” <i>Business &#38; Information Systems Engineering</i>, vol. 64, no. 4, 2022, pp. 421–39.","ama":"Kundisch D, Muntermann J, Oberländer AM, et al. An update for taxonomy designers: Methodological guidance from information systems research. <i>Business &#38; Information Systems Engineering</i>. 2022;64(4):421-439.","bibtex":"@article{Kundisch_Muntermann_Oberländer_Rau_Röglinger_Schoormann_Szopinski_2022, title={An update for taxonomy designers: Methodological guidance from information systems research}, volume={64}, number={4}, journal={Business &#38; Information Systems Engineering}, author={Kundisch, Dennis and Muntermann, J. and Oberländer, A. M. and Rau, D. and Röglinger, M. and Schoormann, T. and Szopinski, Daniel}, year={2022}, pages={421–439} }"},"project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area C","_id":"4"},{"name":"SFB 901 - Subproject C5","_id":"17"}],"language":[{"iso":"eng"}],"title":"An update for taxonomy designers: Methodological guidance from information systems research","year":"2022","author":[{"full_name":"Kundisch, Dennis","first_name":"Dennis","last_name":"Kundisch","id":"21117"},{"last_name":"Muntermann","first_name":"J.","full_name":"Muntermann, J."},{"full_name":"Oberländer, A. M.","first_name":"A. M.","last_name":"Oberländer"},{"full_name":"Rau, D.","first_name":"D.","last_name":"Rau"},{"full_name":"Röglinger, M.","first_name":"M.","last_name":"Röglinger"},{"last_name":"Schoormann","first_name":"T.","full_name":"Schoormann, T."},{"first_name":"Daniel","last_name":"Szopinski","full_name":"Szopinski, Daniel","id":"36372"}],"publication_status":"published","date_updated":"2022-10-21T12:57:05Z","intvolume":"        64","file":[{"file_id":"27282","success":1,"content_type":"application/pdf","file_name":"Kundisch2021_Article_AnUpdateForTaxonomyDesigners.pdf","access_level":"closed","file_size":511483,"relation":"main_file","date_updated":"2021-11-08T12:24:31Z","date_created":"2021-11-08T12:24:31Z","creator":"abursig"}],"date_created":"2021-08-30T10:00:24Z","type":"journal_article","department":[{"_id":"276"}],"publication":"Business & Information Systems Engineering","issue":"4"},{"language":[{"iso":"eng"}],"_id":"33884","user_id":"16205","author":[{"id":"50293","full_name":"Laux, Florian","last_name":"Laux","first_name":"Florian"},{"id":"21117","first_name":"Dennis","last_name":"Kundisch","full_name":"Kundisch, Dennis"}],"conference":{"location":"Copenhagen, Denmark","name":"Pre-ICIS Global Sourcing Workshop 2022"},"title":"Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting","year":"2022","status":"public","publication_status":"accepted","date_updated":"2022-10-26T10:05:24Z","date_created":"2022-10-26T10:04:29Z","department":[{"_id":"276"}],"type":"conference_abstract","citation":{"short":"F. Laux, D. Kundisch, in: n.d.","chicago":"Laux, Florian, and Dennis Kundisch. “Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting,” n.d.","ieee":"F. Laux and D. Kundisch, “Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting,” presented at the Pre-ICIS Global Sourcing Workshop 2022, Copenhagen, Denmark.","apa":"Laux, F., &#38; Kundisch, D. (n.d.). <i>Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting</i>. Pre-ICIS Global Sourcing Workshop 2022, Copenhagen, Denmark.","bibtex":"@inproceedings{Laux_Kundisch, title={Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting}, author={Laux, Florian and Kundisch, Dennis} }","ama":"Laux F, Kundisch D. Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting.","mla":"Laux, Florian, and Dennis Kundisch. <i>Judgment or Choice? An Experimental Comparison of Evaluation Approaches for External Crowdvoting</i>."},"project":[{"_id":"98","grant_number":"EFRE-0801915","name":"Intelligentes Assistenzsystem zur Unterstützung der digitalen Transformation von Geschäftsmodellen"}]},{"main_file_link":[{"url":"https://dl.acm.org/doi/pdf/10.1145/3567430"}],"language":[{"iso":"eng"}],"doi":"10.1145/3567430","year":"2022","title":"Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal","author":[{"last_name":"Kucklick","first_name":"Jan-Peter","full_name":"Kucklick, Jan-Peter","id":"77066"},{"id":"72849","last_name":"Müller","first_name":"Oliver","full_name":"Müller, Oliver"}],"publication_identifier":{"issn":["2158-656X","2158-6578"]},"date_updated":"2023-01-10T05:20:18Z","publication_status":"published","article_type":"original","date_created":"2023-01-10T05:16:02Z","type":"journal_article","keyword":["Interpretability","Convolutional Neural Network","Accuracy-Interpretability Trade-Of","Real Estate Appraisal","Hedonic Pricing","Grad-Ram"],"department":[{"_id":"195"},{"_id":"196"}],"publication":"ACM Transactions on Management Information Systems","abstract":[{"lang":"eng","text":"Deep learning models fuel many modern decision support systems, because they typically provide high predictive performance. Among other domains, deep learning is used in real-estate appraisal, where it allows to extend the analysis from hard facts only (e.g., size, age) to also consider more implicit information about the location or appearance of houses in the form of image data. However, one downside of deep learning models is their intransparent mechanic of decision making, which leads to a trade-off between accuracy and interpretability. This limits their applicability for tasks where a justification of the decision is necessary. Therefore, in this paper, we first combine different perspectives on interpretability into a multi-dimensional framework for a socio-technical perspective on explainable artificial intelligence. Second, we measure the performance gains of using multi-view deep learning which leverages additional image data (satellite images) for real estate appraisal. Third, we propose and test a novel post-hoc explainability method called Grad-Ram. This modified version of Grad-Cam mitigates the intransparency of convolutional neural networks (CNNs) for predicting continuous outcome variables. With this, we try to reduce the accuracy-interpretability trade-off of multi-view deep learning models. Our proposed network architecture outperforms traditional hedonic regression models by 34% in terms of MAE. Furthermore, we find that the used satellite images are the second most important predictor after square feet in our model and that the network learns interpretable patterns about the neighborhood structure and density."}],"_id":"35620","publisher":"Association for Computing Machinery (ACM)","user_id":"77066","status":"public","citation":{"bibtex":"@article{Kucklick_Müller_2022, title={Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal}, DOI={<a href=\"https://doi.org/10.1145/3567430\">10.1145/3567430</a>}, journal={ACM Transactions on Management Information Systems}, publisher={Association for Computing Machinery (ACM)}, author={Kucklick, Jan-Peter and Müller, Oliver}, year={2022} }","ama":"Kucklick J-P, Müller O. Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal. <i>ACM Transactions on Management Information Systems</i>. Published online 2022. doi:<a href=\"https://doi.org/10.1145/3567430\">10.1145/3567430</a>","mla":"Kucklick, Jan-Peter, and Oliver Müller. “Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-Based Real Estate Appraisal.” <i>ACM Transactions on Management Information Systems</i>, Association for Computing Machinery (ACM), 2022, doi:<a href=\"https://doi.org/10.1145/3567430\">10.1145/3567430</a>.","chicago":"Kucklick, Jan-Peter, and Oliver Müller. “Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-Based Real Estate Appraisal.” <i>ACM Transactions on Management Information Systems</i>, 2022. <a href=\"https://doi.org/10.1145/3567430\">https://doi.org/10.1145/3567430</a>.","short":"J.-P. Kucklick, O. Müller, ACM Transactions on Management Information Systems (2022).","ieee":"J.-P. Kucklick and O. Müller, “Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal,” <i>ACM Transactions on Management Information Systems</i>, 2022, doi: <a href=\"https://doi.org/10.1145/3567430\">10.1145/3567430</a>.","apa":"Kucklick, J.-P., &#38; Müller, O. (2022). Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal. <i>ACM Transactions on Management Information Systems</i>. <a href=\"https://doi.org/10.1145/3567430\">https://doi.org/10.1145/3567430</a>"}},{"doi":"10.1007/s12525-022-00530-6","language":[{"iso":"eng"}],"intvolume":"        32","publication_status":"published","date_updated":"2023-01-10T10:12:09Z","publication_identifier":{"issn":["1019-6781","1422-8890"]},"author":[{"full_name":"Bartelheimer, Christian","first_name":"Christian","last_name":"Bartelheimer"},{"first_name":"Philipp","last_name":"zur Heiden","full_name":"zur Heiden, Philipp"},{"full_name":"Lüttenberg, Hedda","first_name":"Hedda","last_name":"Lüttenberg"},{"full_name":"Beverungen, Daniel","last_name":"Beverungen","first_name":"Daniel"}],"year":"2022","title":"Systematizing the lexicon of platforms in information systems: a data-driven study","department":[{"_id":"526"}],"type":"journal_article","keyword":["Management of Technology and Innovation","Marketing","Computer Science Applications","Economics and Econometrics","Business and International Management"],"date_created":"2023-01-10T10:10:17Z","abstract":[{"lang":"eng","text":"<jats:title>Abstract</jats:title><jats:p>While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.</jats:p>"}],"publication":"Electronic Markets","issue":"1","volume":32,"user_id":"21671","_id":"35740","publisher":"Springer Science and Business Media LLC","page":"375-396","status":"public","citation":{"ieee":"C. Bartelheimer, P. zur Heiden, H. Lüttenberg, and D. Beverungen, “Systematizing the lexicon of platforms in information systems: a data-driven study,” <i>Electronic Markets</i>, vol. 32, no. 1, pp. 375–396, 2022, doi: <a href=\"https://doi.org/10.1007/s12525-022-00530-6\">10.1007/s12525-022-00530-6</a>.","apa":"Bartelheimer, C., zur Heiden, P., Lüttenberg, H., &#38; Beverungen, D. (2022). Systematizing the lexicon of platforms in information systems: a data-driven study. <i>Electronic Markets</i>, <i>32</i>(1), 375–396. <a href=\"https://doi.org/10.1007/s12525-022-00530-6\">https://doi.org/10.1007/s12525-022-00530-6</a>","chicago":"Bartelheimer, Christian, Philipp zur Heiden, Hedda Lüttenberg, and Daniel Beverungen. “Systematizing the Lexicon of Platforms in Information Systems: A Data-Driven Study.” <i>Electronic Markets</i> 32, no. 1 (2022): 375–96. <a href=\"https://doi.org/10.1007/s12525-022-00530-6\">https://doi.org/10.1007/s12525-022-00530-6</a>.","short":"C. Bartelheimer, P. zur Heiden, H. Lüttenberg, D. Beverungen, Electronic Markets 32 (2022) 375–396.","mla":"Bartelheimer, Christian, et al. “Systematizing the Lexicon of Platforms in Information Systems: A Data-Driven Study.” <i>Electronic Markets</i>, vol. 32, no. 1, Springer Science and Business Media LLC, 2022, pp. 375–96, doi:<a href=\"https://doi.org/10.1007/s12525-022-00530-6\">10.1007/s12525-022-00530-6</a>.","bibtex":"@article{Bartelheimer_zur Heiden_Lüttenberg_Beverungen_2022, title={Systematizing the lexicon of platforms in information systems: a data-driven study}, volume={32}, DOI={<a href=\"https://doi.org/10.1007/s12525-022-00530-6\">10.1007/s12525-022-00530-6</a>}, number={1}, journal={Electronic Markets}, publisher={Springer Science and Business Media LLC}, author={Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda and Beverungen, Daniel}, year={2022}, pages={375–396} }","ama":"Bartelheimer C, zur Heiden P, Lüttenberg H, Beverungen D. Systematizing the lexicon of platforms in information systems: a data-driven study. <i>Electronic Markets</i>. 2022;32(1):375-396. doi:<a href=\"https://doi.org/10.1007/s12525-022-00530-6\">10.1007/s12525-022-00530-6</a>"}},{"related_material":{"link":[{"relation":"research_paper","url":"https://aisel.aisnet.org/acis2022/81/"}]},"publication":"Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022)","citation":{"mla":"Arslan, Kader, and Matthias Trier. “Towards a Process Model for Social Media Marketing.” <i>Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022)</i>, 2022.","bibtex":"@inproceedings{Arslan_Trier_2022, place={Melbourne, Australia}, title={Towards a Process Model for Social Media Marketing}, booktitle={Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022)}, author={Arslan, Kader and Trier, Matthias}, year={2022} }","ama":"Arslan K, Trier M. Towards a Process Model for Social Media Marketing. In: <i>Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022)</i>. ; 2022.","ieee":"K. Arslan and M. Trier, “Towards a Process Model for Social Media Marketing,” presented at the ACIS 2022, Melbourne, Australia, 2022.","apa":"Arslan, K., &#38; Trier, M. (2022). Towards a Process Model for Social Media Marketing. <i>Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022)</i>. ACIS 2022, Melbourne, Australia.","chicago":"Arslan, Kader, and Matthias Trier. “Towards a Process Model for Social Media Marketing.” In <i>Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022)</i>. Melbourne, Australia, 2022.","short":"K. Arslan, M. Trier, in: Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022), Melbourne, Australia, 2022."},"type":"conference","keyword":["Social media","Social media marketing process","Social media strategy","Social media management","Guidelines"],"department":[{"_id":"198"}],"place":"Melbourne, Australia","date_created":"2022-12-10T15:32:15Z","date_updated":"2023-12-26T11:06:43Z","publication_status":"published","title":"Towards a Process Model for Social Media Marketing","year":"2022","status":"public","conference":{"name":"ACIS 2022","location":"Melbourne, Australia"},"author":[{"full_name":"Arslan, Kader","last_name":"Arslan","first_name":"Kader","id":"20388"},{"last_name":"Trier","first_name":"Matthias","full_name":"Trier, Matthias","id":"72744"}],"user_id":"20388","language":[{"iso":"eng"}],"_id":"34317"},{"_id":"36912","language":[{"iso":"eng"}],"doi":"10.1007/978-3-031-16103-2_18","user_id":"51905","author":[{"id":"56760","last_name":"Löhr","first_name":"Bernd","full_name":"Löhr, Bernd"},{"last_name":"Brennig","first_name":"Katharina","full_name":"Brennig, Katharina","id":"51905"},{"id":"49160","last_name":"Bartelheimer","first_name":"Christian","full_name":"Bartelheimer, Christian"},{"first_name":"Daniel","last_name":"Beverungen","full_name":"Beverungen, Daniel","id":"59677"},{"first_name":"Oliver","last_name":"Müller","full_name":"Müller, Oliver","id":"72849"}],"publication_identifier":{"isbn":["978-3-031-16103-2"]},"year":"2022","status":"public","title":"Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing","date_updated":"2024-01-11T11:35:54Z","date_created":"2023-01-16T11:04:54Z","department":[{"_id":"196"}],"type":"conference","citation":{"apa":"Löhr, B., Brennig, K., Bartelheimer, C., Beverungen, D., &#38; Müller, O. (2022). Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing. <i>International Conference on Business Process Management</i>. <a href=\"https://doi.org/10.1007/978-3-031-16103-2_18\">https://doi.org/10.1007/978-3-031-16103-2_18</a>","ieee":"B. Löhr, K. Brennig, C. Bartelheimer, D. Beverungen, and O. Müller, “Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing,” 2022, doi: <a href=\"https://doi.org/10.1007/978-3-031-16103-2_18\">10.1007/978-3-031-16103-2_18</a>.","short":"B. Löhr, K. Brennig, C. Bartelheimer, D. Beverungen, O. Müller, in: International Conference on Business Process Management, 2022.","chicago":"Löhr, Bernd, Katharina Brennig, Christian Bartelheimer, Daniel Beverungen, and Oliver Müller. “Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing.” In <i>International Conference on Business Process Management</i>, 2022. <a href=\"https://doi.org/10.1007/978-3-031-16103-2_18\">https://doi.org/10.1007/978-3-031-16103-2_18</a>.","mla":"Löhr, Bernd, et al. “Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing.” <i>International Conference on Business Process Management</i>, 2022, doi:<a href=\"https://doi.org/10.1007/978-3-031-16103-2_18\">10.1007/978-3-031-16103-2_18</a>.","ama":"Löhr B, Brennig K, Bartelheimer C, Beverungen D, Müller O. Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing. In: <i>International Conference on Business Process Management</i>. ; 2022. doi:<a href=\"https://doi.org/10.1007/978-3-031-16103-2_18\">10.1007/978-3-031-16103-2_18</a>","bibtex":"@inproceedings{Löhr_Brennig_Bartelheimer_Beverungen_Müller_2022, title={Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-16103-2_18\">10.1007/978-3-031-16103-2_18</a>}, booktitle={International Conference on Business Process Management}, author={Löhr, Bernd and Brennig, Katharina and Bartelheimer, Christian and Beverungen, Daniel and Müller, Oliver}, year={2022} }"},"publication":"International Conference on Business Process Management","abstract":[{"text":"Existing process mining methods are primarily designed for processes that have reached a high degree of digitalization and standardization. In contrast, the literature has only begun to discuss how process mining can be applied to knowledge-intensive processes—such as product innovation processes—that involve creative activities, require organizational flexibility, depend on single actors’ decision autonomy, and target process-external goals such as customer satisfaction. Due to these differences, existing Process Mining methods cannot be applied out-of-the-box to analyze knowledge-intensive processes. In this paper, we employ Action Design Research (ADR) to design and evaluate a process mining approach for knowledge-intensive processes. More specifically, we draw on the two processes of product innovation and engineer-to-order in manufacturing contexts. We collected data from 27 interviews and conducted 49 workshops to evaluate our IT artifact at different stages in the ADR process. From a theoretical perspective, we contribute five design principles and a conceptual artifact that prescribe how process mining ought to be designed for knowledge-intensive processes in manufacturing. From a managerial perspective, we demonstrate how enacting these principles enables their application in practice.","lang":"eng"}]},{"doi":"10.1109/bigdata55660.2022.10020933","user_id":"60721","main_file_link":[{"url":"https://ieeexplore.ieee.org/document/10020933"}],"publisher":"IEEE","_id":"42631","language":[{"iso":"eng"}],"date_updated":"2024-01-15T12:32:06Z","publication_status":"published","status":"public","year":"2022","title":"Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift","conference":{"end_date":"2022-12-20","location":"Osaka, Japan","start_date":"2022-12-17","name":"2022 IEEE International Conference on Big Data (Big Data)"},"author":[{"id":"60721","full_name":"Caron, Matthew","last_name":"Caron","first_name":"Matthew"}],"publication_identifier":{"eisbn":["978-1-6654-8045-1"]},"type":"conference","department":[{"_id":"196"}],"date_created":"2023-02-28T08:29:30Z","abstract":[{"text":"In recent years, many cases of deep neural networks failing dramatically when faced with adversarial or real-world examples have been reported. Such failures, which are quite hard to detect, are often related to a generalization problem known as shortcut learning. Yet, with state-of-the-art transformer models now being ubiquitous in financial text mining, one cannot help but wonder how reliable the results conveyed in the ever-growing literature genuinely are. Against this background, we expose, in this work, how vulnerable contemporary financial text mining approaches are to shortcut learning. Focussing on the common learning task of financial sentiment classification, we assess, using two entity-based sampling strategies and our publicly-available dataset, the discrepancies between i.i.d. and o.o.d. performance estimates of four transformer models. Our results reveal that o.o.d. performance estimates are consistently weaker than those of their i.i.d. counterparts, with the error rate increasing by as much as 29.7%, thus, demonstrating how this issue can, when overlooked, lead to misleading evaluations. Moreover, we show how additional preprocessing steps, such as entity removal and vocabulary filtering, can help reduce the effects of shortcut learning by filtering out entity-related linguistic cues.","lang":"eng"}],"publication":"2022 IEEE International Conference on Big Data (Big Data)","citation":{"chicago":"Caron, Matthew. “Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift.” In <i>2022 IEEE International Conference on Big Data (Big Data)</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/bigdata55660.2022.10020933\">https://doi.org/10.1109/bigdata55660.2022.10020933</a>.","short":"M. Caron, in: 2022 IEEE International Conference on Big Data (Big Data), IEEE, 2022.","apa":"Caron, M. (2022). Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift. <i>2022 IEEE International Conference on Big Data (Big Data)</i>. 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan. <a href=\"https://doi.org/10.1109/bigdata55660.2022.10020933\">https://doi.org/10.1109/bigdata55660.2022.10020933</a>","ieee":"M. Caron, “Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift,” presented at the 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, 2022, doi: <a href=\"https://doi.org/10.1109/bigdata55660.2022.10020933\">10.1109/bigdata55660.2022.10020933</a>.","ama":"Caron M. Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift. In: <i>2022 IEEE International Conference on Big Data (Big Data)</i>. IEEE; 2022. doi:<a href=\"https://doi.org/10.1109/bigdata55660.2022.10020933\">10.1109/bigdata55660.2022.10020933</a>","bibtex":"@inproceedings{Caron_2022, title={Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift}, DOI={<a href=\"https://doi.org/10.1109/bigdata55660.2022.10020933\">10.1109/bigdata55660.2022.10020933</a>}, booktitle={2022 IEEE International Conference on Big Data (Big Data)}, publisher={IEEE}, author={Caron, Matthew}, year={2022} }","mla":"Caron, Matthew. “Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift.” <i>2022 IEEE International Conference on Big Data (Big Data)</i>, IEEE, 2022, doi:<a href=\"https://doi.org/10.1109/bigdata55660.2022.10020933\">10.1109/bigdata55660.2022.10020933</a>."}},{"abstract":[{"text":"Our world is more connected than ever before. Sadly, however, this highly connected world has made it easier to bully, insult, and propagate hate speech on the cyberspace. Even though researchers and companies alike have started investigating this real-world problem, the question remains as to why users are increasingly being exposed to hate and discrimination online. In fact, the noticeable and persistent increase in harmful language on social media platforms indicates that the situation is, actually, only getting worse. Hence, in this work, we show that contemporary ML methods can help tackle this challenge in an accurate and cost-effective manner. Our experiments demonstrate that a universal approach combining transfer learning methods and state-of-the-art Transformer architectures can trigger the efficient development of toxic language detection models. Consequently, with this universal approach, we provide platform providers with a simplistic approach capable of enabling the automated moderation of user-generated content, and as a result, hope to contribute to making the web a safer place.","lang":"eng"}],"publication":"55th Hawaii International Conference on System Sciences (HICSS)","citation":{"apa":"Caron, M., Bäumer, F. S., &#38; Müller, O. (2022). Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models. <i>55th Hawaii International Conference on System Sciences (HICSS)</i>. 55th Hawaii International Conference on System Sciences (HICSS), Online.","ieee":"M. Caron, F. S. Bäumer, and O. Müller, “Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models,” presented at the 55th Hawaii International Conference on System Sciences (HICSS), Online, 2022.","short":"M. Caron, F.S. Bäumer, O. Müller, in: 55th Hawaii International Conference on System Sciences (HICSS), 2022.","chicago":"Caron, Matthew, Frederik S. Bäumer, and Oliver Müller. “Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models.” In <i>55th Hawaii International Conference on System Sciences (HICSS)</i>, 2022.","mla":"Caron, Matthew, et al. “Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models.” <i>55th Hawaii International Conference on System Sciences (HICSS)</i>, 2022.","ama":"Caron M, Bäumer FS, Müller O. Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models. In: <i>55th Hawaii International Conference on System Sciences (HICSS)</i>. ; 2022.","bibtex":"@inproceedings{Caron_Bäumer_Müller_2022, title={Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models}, booktitle={55th Hawaii International Conference on System Sciences (HICSS)}, author={Caron, Matthew and Bäumer, Frederik S. and Müller, Oliver}, year={2022} }"},"type":"conference","department":[{"_id":"196"}],"date_created":"2021-09-29T10:06:24Z","date_updated":"2024-01-15T12:37:10Z","publication_status":"published","status":"public","year":"2022","title":"Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models","conference":{"location":"Online","start_date":"2022-01-03","name":"55th Hawaii International Conference on System Sciences (HICSS)","end_date":"2022-01-07"},"author":[{"id":"60721","first_name":"Matthew","last_name":"Caron","full_name":"Caron, Matthew"},{"first_name":"Frederik S.","last_name":"Bäumer","full_name":"Bäumer, Frederik S."},{"id":"72849","full_name":"Müller, Oliver","first_name":"Oliver","last_name":"Müller"}],"user_id":"60721","main_file_link":[{"url":"http://hdl.handle.net/10125/79428"}],"_id":"25113","language":[{"iso":"eng"}]},{"publication":"Socio-Economic Planning Sciences","date_created":"2024-04-04T15:50:16Z","type":"journal_article","keyword":["Management Science and Operations Research","Statistics","Probability and Uncertainty","Strategy and Management","Economics and Econometrics","Geography","Planning and Development"],"department":[{"_id":"277"}],"title":"A private sustainable partner selection model for green public-private partnerships and regional economic development","year":"2022","publication_identifier":{"issn":["0038-0121"]},"author":[{"full_name":"Tavana, Madjid","first_name":"Madjid","last_name":"Tavana","id":"31858"},{"full_name":"Khalili Nasr, Arash","last_name":"Khalili Nasr","first_name":"Arash"},{"first_name":"Hassan","last_name":"Mina","full_name":"Mina, Hassan"},{"full_name":"Michnik, Jerzy","last_name":"Michnik","first_name":"Jerzy"}],"publication_status":"published","date_updated":"2024-04-15T13:16:33Z","intvolume":"        83","article_number":"101189","language":[{"iso":"eng"}],"doi":"10.1016/j.seps.2021.101189","citation":{"ieee":"M. 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A multicriteria-optimization model for cultural heritage renovation projects and public-private partnerships in the hospitality industry. <i>Current Issues in Tourism</i>, <i>25</i>(22), 3709–3734. <a href=\"https://doi.org/10.1080/13683500.2021.2015299\">https://doi.org/10.1080/13683500.2021.2015299</a>","ieee":"M. Tavana, A. Azadmanesh, A. K. Nasr, and H. Mina, “A multicriteria-optimization model for cultural heritage renovation projects and public-private partnerships in the hospitality industry,” <i>Current Issues in Tourism</i>, vol. 25, no. 22, pp. 3709–3734, 2022, doi: <a href=\"https://doi.org/10.1080/13683500.2021.2015299\">10.1080/13683500.2021.2015299</a>.","short":"M. Tavana, A. Azadmanesh, A.K. Nasr, H. 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