- Corpora - ELRA lists

Edge Hill Corpus Research Group, Thursday 29 February 2024, 2:00-3:30 pm (GMT)
by Costas Gabrielatos 10 Feb '24

10 Feb '24

The next meeting of the Edge Hill Corpus Research Group will take place online (via MS Teams) on Thursday 29 February 2024, 2:00-3:30 pm (GMT). Attendance is free. You can register here: https://store.edgehill.ac.uk/conferences-and-events/conferences/events/edge… Registration closes on Wednesday 28 February, 11 am (GMT) Topic: Corpus Methodology Speaker: Matteo Di Cristofaro<https://infogrep.it/site/> (University of Modena and Reggio Emilia, Italy) Title: One dataset, many corpora: Problems of scientific validity in corpora and corpus-derived results Abstract Corpus linguistics has, since its inception, recognised the relevance of digital technologies as a major driving force behind corpus techniques and their (r)evolution in the study of language (cf. Tognini-Bonelli 2012). And yet, while both corpus linguistics and digital technologies have frequently benefited from each other (the case of NLP/NLU is one such macro example), their pathways have often diverged. The result is a disconnect between corpus linguistics and digital data processing whose effects directly impinge on the ability to analyse language through software tools. A disconnect becoming more and more relevant as corpus linguistics is being applied to vast amounts of data obtained from manifold sources – including a wide array of social media platforms, each one with its unique linguistic and technical peculiarities. As the ground-truth of an ever-increasing number of language studies, corpora must be able to correctly treat and represent such peculiarities: e.g. the dialogic dimension of comments or forum posts; the presence (and potential subsequent normalisation) of spelling variations; the use of hashtags and emojis. Failing to do so, the corpus-derived results will likely present researchers with a falsified view of the language under scrutiny. What is at stake is not the ability to “count” what is in a corpus, but rather whether what is being counted is or is not a feature present in the original data – of which the corpus should be a faithful representation. The presentation is consequently devoted to tackling digital technicalities, i.e. “those notions and mechanisms that – while not classically associated with natural language – are i) foundational of the digital environments in which language production and exchanges occur and ii) at the core of the techniques that are used to produce, collect, and process the focus of investigation, that is, digital textual data.” (Di Cristofaro 2023:5). One such example is represented by character encodings: although at the “core” of the whole corpus linguistics enterprise (cf. McEnery and Xiao 2005; Gries 2016:39,111) – since they allow written language to be processed by a computer and understood by humans -, these are often overlooked at all stages of corpus compilation and analysis, potentially leading linguists to involuntarily tampering with the data and its linguistic contents. Starting from practical examples, the presentation discusses the implications that digital technicalities have on corpora and their analyses – or rather, what happens when they are not properly treated – while outlining (also in the form of Python scripts and practical tools) potential new pathways that a “digital-aware” perspective of corpus linguistics can open up. References Di Cristofaro, Matteo. Corpus Approaches to Language in Social Media. Routledge Advances in Corpus Linguistics. New York: Routledge, 2023. https://doi.org/10.4324/9781003225218<https://doi.org/10.4324/9781003225218>. Gries, Stefan Th. Quantitative Corpus Linguistics with R: A Practical Introduction. 2nd ed. New York: Routledge, 2016. https://doi.org/10.4324/9781315746210<https://doi.org/10.4324/9781315746210>. McEnery, Tony, and Richard Xiao. ‘Character Encoding in Corpus Construction’. In Developing Linguistic Corpora: A Guide to Good Practice, edited by Martin Wynne, 47–58. Oxford: Oxbow Books, 2005. https://users.ox.ac.uk/~martinw/dlc/index.htm<https://users.ox.ac.uk/~martinw/dlc/index.htm>. Tognini Bonelli, Elena. ‘Theoretical Overview of the Evolution of Corpus Linguistics’. In The Routledge Handbook of Corpus Linguistics, edited by Anne O’Keeffe and Michael McCarthy, 14–27. Routledge Handbooks in Applied Linguistics. Milton Park, Abingdon, Oxon ; New York: Routledge, 2012. ________________________________ Edge Hill University<http://ehu.ac.uk/home/emailfooter> Modern University of the Year, The Times and Sunday Times Good University Guide 2022<http://ehu.ac.uk/tef/emailfooter> University of the Year, Educate North 2021/21 ________________________________ This message is private and confidential. If you have received this message in error, please notify the sender and remove it from your system. Any views or opinions presented are solely those of the author and do not necessarily represent those of Edge Hill or associated companies. Edge Hill University may monitor email traffic data and also the content of email for the purposes of security and business communications during staff absence.<http://ehu.ac.uk/itspolicies/emailfooter>

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Call for Contributions HealTAC2024
by d.harvey4＠lancaster.ac.uk 09 Feb '24

09 Feb '24

HealTAC 2024 (the 7th Healthcare Text Analytics Conference) is taking place in Lancaster (UK), from June 12 to June 14th, 2024. Submit your extended abstracts that describe any aspect of healthcare text analytics by March 28th. Submissions (up to 2 pages) should be prepared based on a template that is available at the conference web site: https://healtac2024.github.io/submissions/ We also invite PhD and fellowship project submissions that describe ongoing PhD research (any stage) or a planned fellowship application. The conference will provide an opportunity to receive constructive feedback from a panel of experts. As in previous years, there will be a post-conference open call to submit a journal length paper for further peer review and publication in Frontiers in Digital Health. We are looking forward to seeing you at #HEALTAC2024

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Webminar by Heng Ji (University of Illinois)
by HiTZ zentroa 09 Feb '24

09 Feb '24

**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. **** Dear colleague, We are happy to announce the next webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). You can check the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars Next webinar: * *Speaker*: Heng Ji (University of Illinois) * *Title*: SmartBook: an AI Prophetess for Disaster Reporting and Forecasting * *Date*: *Friday*, February 16, 2024 - 15:00 CET * *Summary*: History repeats itself, sometimes in a bad way. If we don’t learn lessons from history, we might suffer similar tragedies, which are often preventable. For example, many experts now agree that some schools were closed for too long during COVID-19 and that abruptly removing millions of children from American classrooms has had harmful effects on their emotional and intellectual health. Also many wish we had invested in vaccines earlier, prepared more personal protective equipment and medical facilities, provided online consultation services for people who suffered from anxiety and depression, and created better online education platforms for students. Similarly, genocides throughout history (from those in World War II to the recent one in Rwanda in 1994) have also all shared early warning signs (e.g., organization of hate groups, militias, and armies and polarization of the population) forming patterns that follow discernible progressions. Preventing natural or man-made disasters requires being aware of these patterns and taking pre-emptive action to address and reduce them, or ideally, eliminate them. Emerging events, such as the COVID pandemic and the Ukraine Crisis, require a time-sensitive comprehensive understanding of the situation to allow for appropriate decision-making and effective action response. Automated generation of situation reports can significantly reduce the time, effort, and cost for domain experts when preparing their official human-curated reports. However, AI research toward this goal has been very limited, and no successful trials have yet been conducted to automate such report generation and “what-if” disaster forecasting. Pre-existing natural language processing and information retrieval techniques are insufficient to identify, locate, and summarize important information, and lack detailed, structured, and strategic awareness. We propose SmartBook, a novel framework that cannot be solved by ChatGPT, targeting situation report generation which consumes large volumes of news data to produce a structured situation report with multiple hypotheses (claims) summarized and grounded with rich links to factual evidence by claim detection, fact checking, misinformation detection and factual error correction. Furthermore, SmartBook can also serve as a novel news event simulator, or an intelligent prophetess. Given “What-if” conditions and dimensions elicited from a domain expert user concerning a disaster scenario, SmartBook will induce schemas from historical events, and automatically generate a complex event graph along with a timeline of news articles that describe new simulated events based on a new Λ-shaped attention mask that can generate text with infinite length. By effectively simulating disaster scenarios in both event graph and natural language format, we expect SmartBook will greatly assist humanitarian workers and policymakers to exercise reality checks (what would the next disaster look like under these given conditions?), and thus better prevent and respond to future disasters. * *Bio*: Heng Ji is a professor at Computer Science Department, and an affiliated faculty member at Electrical and Computer Engineering Department and Coordinated Science Laboratory of University of Illinois Urbana-Champaign. She is an Amazon Scholar. She is the Founding Director of Amazon-Illinois Center on AI for Interactive Conversational Experiences (AICE). She received her B.A. and M. A. in Computational Linguistics from Tsinghua University, and her M.S. and Ph.D. in Computer Science from New York University. Her research interests focus on Natural Language Processing, especially on Multimedia Multilingual Information Extraction, Knowledge-enhanced Large Language Models, Knowledge-driven Generation and Conversational AI. She was selected as a Young Scientist to attend the 6th World Laureates Association Forum, and selected to participate in DARPA AI Forward in 2023. She was selected as "Young Scientist" and a member of the Global Future Council on the Future of Computing by the World Economic Forum in 2016 and 2017. She was named as part of Women Leaders of Conversational AI (Class of 2023) by Project Voice. The awards she received include "AI's 10 to Watch" Award by IEEE Intelligent Systems in 2013, NSF CAREER award in 2009, PACLIC2012 Best paper runner-up, "Best of ICDM2013" paper award, "Best of SDM2013" paper award, ACL2018 Best Demo paper nomination, ACL2020 Best Demo Paper Award, NAACL2021 Best Demo Paper Award, Google Research Award in 2009 and 2014, IBM Watson Faculty Award in 2012 and 2014 and Bosch Research Award in 2014-2018. She was invited by the Secretary of the U.S. Air Force and AFRL to join Air Force Data Analytics Expert Panel to inform the Air Force Strategy 2030, and invited to speak at the Federal Information Integrity R&D Interagency Working Group (IIRD IWG) briefing in 2023. She is the lead of many multi-institution projects and tasks, including the U.S. ARL projects on information fusion and knowledge networks construction, DARPA ECOLE MIRACLE team, DARPA KAIROS RESIN team and DARPA DEFT Tinker Bell team. She has coordinated the NIST TAC Knowledge Base Population task since 2010-2021. She was the associate editor for IEEE/ACM Transaction on Audio, Speech, and Language Processing, and served as the Program Committee Co-Chair of many conferences including NAACL-HLT2018 and AACL-IJCNLP2022. She is elected as the North American Chapter of the Association for Computational Linguistics (NAACL) secretary 2020-2023. Her research has been widely supported by the U.S. government agencies (DARPA, NSF, DoE, ARL, IARPA, AFRL, DHS) and industry (Amazon, Google, Facebook, Bosch, IBM, Disney). * *Upcoming webinars: * Smaranda Muresan (March 7, 2024) * Ralf Schlüter (May 2, 2024) * Marco Baroni (June 6, 2024) Check past and upcoming webinars at the following url: http://www.hitz.eus/webinars If you are interested in participating, please complete this registration form: http://www.hitz.eus/webinar_izenematea If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info Best wishes, HiTZ Zentroa P.S:HiTZ will not grant any type of certificate for attendance at these webinars.

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First Call For Papers and Participation: BioNLP 2024 and Shared Tasks @ ACL 2024
by dina demner 09 Feb '24

09 Feb '24

BIONLP 2024 and Shared Tasks @ ACL 2024 https://aclweb.org/aclwiki/BioNLP_Workshop *Tentative* Important Dates (All submission deadlines are 11:59 p.m. UTC-12:00 “anywhere on Earth”) Paper submission deadline: May 17 (Friday), 2024 Notification of acceptance: June 17 (Monday), 2024 Camera-ready paper due: July 1 (Monday), 2024 Workshop: August 16, 2024, Location: LOTUS SUITE 12 Please watch for the updates! SUBMISSION INSTRUCTIONS ----------------------------------------- Two types of submissions are invited: full papers and short papers. Full papers should not exceed eight (8) pages of text, plus unlimited references. These are intended to be reports of original research. BioNLP aims to be the forum for interesting, innovative, and promising work involving biomedicine and language technology, whether or not yielding high performance at the moment. This by no means precludes our interest in and preference for mature results, strong performance, and thorough evaluation. Both types of research and combinations thereof are encouraged. Short papers may consist of up to four (4) pages of content, plus unlimited references. Appropriate short paper topics include preliminary results, application notes, descriptions of work in progress, etc. Electronic Submission Submissions must be electronic and in PDF format, using the Softconf START conference management system Submissions need to be anonymous. Submission site for the workshop https://softconf.com/acl2024/BioNLP2024 Please follow the ACL formatting guidelines: https://github.com/acl-org/acl-style-files Dual submission policy: papers may NOT be submitted to the BioNLP workshop if they are or will be concurrently submitted to another meeting or publication. INVITED TALK ----------------------------------------- Titipat Achakulvisut. Biomedical and Data (Bio-Data) lab at Mahidol University WORKSHOP OVERVIEW AND SCOPE ----------------------------------------- The BioNLP workshop, associated with the ACL SIGBIOMED special interest group, is an established primary venue for presenting research in language processing and language understanding for the biological and medical domains. The workshop has been running every year since 2002 and continues getting stronger. Many other emerging biomedical and clinical language processing workshops can afford to be more specialized because BioNLP truly encompasses the breadth of the domain and brings together researchers in bio- and clinical NLP from all over the world. BioNLP 2024 will be particularly interested in transparency of the generative approaches and factuality of the generated text. Language processing that supports DEIA (Diversity, Equity, Inclusion and Accessibility) is still of utmost importance. The work on detection and mitigation of bias and misinformation continues to be of interest. Research in languages other than English, particularly, under-represented languages, and health disparities are always of interest to BioNLP. Other active areas of research include, but are not limited to: Tangible results of biomedical language processing applications; Entity identification and normalization (linking) for a broad range of semantic categories; Extraction of complex relations and events; Discourse analysis; Anaphora \& coreference resolution; Text mining \& Literature based discovery; Summarization; Text simplification; Question Answering; Resources and strategies for system testing and evaluation; Infrastructures and pre-trained language models for biomedical NLP; Processing and annotation platforms; Synthetic data generation \& data augmentation; Translating NLP research into practice; Getting reproducible results. SHARED TASKS ----------------------------------------- 1. Clinical Text generation Task 1: Radiology Report Generation An important medical application of natural language generation (NLG) is to build assistive systems that take X-ray images of a patient and generate a textual report describing clinical observations in the images. This is a clinically important task, offering the potential to reduce radiologists’ repetitive work and generally improve clinical communication. This shared task is using the first large-scale collection of RRG datasets based on MIMIC-CXR, CheXpert, PadChest and CANDID-PTX. Participants will need to generate findings and impression from chest x-rays and will be evaluated on a common leaderboard with recent proposed metrics such as F1-Radgraph and RadCliQ. This shared task aims to benchmark recent progress using common data splits and evaluation implementations. See details at https://stanford-aimi.github.io/RRG24/ Task 2: Discharge Me! The primary objective of this task is to reduce the time and effort clinicians spend on writing detailed notes in the electronic health record (EHR). Clinicians play a crucial role in documenting patient progress in discharge summaries, but the creation of concise yet comprehensive hospital course summaries and discharge instructions often demands a significant amount of time, especially since these sections cannot be readily copied from prior notes. This can lead to clinician burnout and operational inefficiencies within hospital workflows. By streamlining the generation of these sections, we can not only enhance the accuracy and completeness of clinical documentation but also significantly reduce the time clinicians spend on administrative tasks, ultimately improving patient care quality. See details at https://stanford-aimi.github.io/discharge-me/ 2. BioLaySumm This shared task surrounds the abstractive summarization of biomedical articles, with an emphasis on catering to non-expert audiences through the generation of summaries that are more readable, containing more background information and less technical terminology (i.e., a “lay summary”). This is the 2nd iteration of BioLaySumm, following the success of the 1st edition of the task at BioNLP 2023 which attracted 56 submissions across 20 different teams. In this edition, we aim to build on last year’s task by introducing a new test set, updating our evaluation protocol, and encouraging participants to explore novel approaches that will help to further advance the state-of-the-art for Lay Summarization. See details at https://biolaysumm.org/ Organizers ----------------------------------------- * Dina Demner-Fushman, US National Library of Medicine * Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK * Makoto Miwa, Toyota Technological Institute, Japan * Kirk Roberts, UTHealth, Houston, Texas * Jun-ichi Tsujii, National Institute of Advanced Industrial Science and Technology, Japan

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Invitation Guest Speaker @ ACFTI Cybersecurity stream
by Andrew Zayine 08 Feb '24

08 Feb '24

On behalf of the Association of Cyber Forensics and Threat Investigators (ACFTI), I am pleased to invite you to the new Cybersecurity stream lecture/seminar series. The presentation is a maximum of 1 hour in length, with an audience of about 60+, made up of undergraduate and postgraduate students plus cybersecurity students from developing countries. Our goal is to shine a spotlight on the broad array of new advances in cybersecurity science and operations currently adopted in the industry. This session will be conducted online. It will be fantastic to have any hands-on topics related to cyber forensics. Your discussion on this topic will be a great addition to our event. Expressions of interest to present from anyone doing research or applying cybersecurity techniques to practical or theoretical applications related to the interactions between cyber forensics and threat investigations can be sent as a summary of your work (c.200 words) to acfti (at) acfti (dot) org by February 15, 2024 Thank you in advance for your consideration, and we are very much looking forward to hearing from you. To get more news about our events, please join our low-traffic announcement group @ https://groups.google.com/g/acfti ________________________________________________________ Association of Cyber Forensics and Threat Investigators https://www.acfti.org Twitter: @acfti

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3rd CfP: Workshop on Reference, Framing, and Perspective
by Pia Sommerauer 08 Feb '24

08 Feb '24

We are very pleased to share our second call for papers for our workshop on Reference, Framing, and Perspective co-located with LREC-COLING 2024. Quick overview: * Workshop website: https://cltl.github.io/reference-framing-perspective/ * When: Saturday, May 25th, 20204 * Where: Torino, Italy (co-located with LREC-COLING 2024) * Deadline for submissions: February 20th, 2024 * Paper types: regular papers (short and long) and extended abstracts * Paper submission link: https://softconf.com/lrec-coling2024/reference-framing-perspective2024/user… * Deadline for camera-ready papers: March 29th, 2024 * Shared dataset: https://github.com/cltl/rfp_corpus_collection When something happens in the world, we have access to an unlimited range of ways (from lexical choices to specific syntactic structures) to refer to the same real-world event. We can chose to express information explicitly or imply it. Variations in reference may convey radically different perspectives. This process of making reference to something by adopting a specific perspective is also known as framing. Although previous work in this area is present (see Ali and Hassan (2022)’s survey for an overview), there is a lack of a unitary framework and only few targeted datasets (Chen et al., 2019) and tools based on Large Language Models exist (Minnema et al., 2022). In this workshop, we propose to adopt Frame Semantics (Fillmore, 1968, 1985, 2006) as a unifying theoretical framework and analysis method to understand the choices made in linguistic references to events. The semantic frames (expressed by predicates and roles) we choose give rise to our understanding, or framing, of an event. We aim to bring together different research communities interested in lexical and syntactic variation, referential grounding, frame semantics, and perspectives. We believe that there is significant overlap within the goals and interests of these communities, but not necessarily the common ground to enable collaborative work. Referentially Grounded Shared Dataset One way to study variation in framing is to conduct contrastive analyses of texts reporting on the same real-world event. Such an analysis can help to reveal the extent of variation in framing and possibly give rise to the underlying factors that lead to different choices in framing the same event. We collected such a corpus about the Eurovision Song Festival and make it available as a Shared Dataset for the Workshop. The purpose of this corpus is to enable exploratory analyses, facilitate discussion among participants, and, last but not least, make our workshop a real working workshop. The corpus is composed of news articles reporting on the Eurovision Song Contest that took place in Rotterdam, the Netherlands (canceled in 2020 and held in 2021). The news articles have been collected using the structured data-to-text approach (Vossen et al., 2018). The corpus contains news articles in multiple languages. We invite participants to submit short and targeted analyses using the data (extended abstracts to be discussed in a hands-on data session). Participants are also free to use the data in regular contributions. Regular contributions: We aim to lay the groundwork for such efforts. We invite contributions (regular long papers of 8 pages or short papers of 4 pages) targeting any of the following - non-exhaustive - list of topics: * Theoretical models of framing and perspective * Annotation frameworks for framing and perspectives * Computational models of framing and perspective * Approaches for creating and analyzing referentially grounded datasets (containing different perspectives, written at different points in time, written in different languages) * Approaches for and analyses of texts about contested and divisive events triggering different opinions and perspectives * Analyses of and methods for analyzing (diachronic) lexical variation and framing * Language resources for reference, frames, and perspectives * Approaches and tools to compare claims of sources * Frames as expressions of bias in the representation of social groups * User interface for the visualization of multiple perspectives Extended abstracts: We invite extended abstracts (1,500 words maximum) about small analyses or experiments conducted on our Shared Data. The abstracts will be non-archival and discussed in a dedicated data session. Invited speakers: Maria Antoniak Vered Shwartz Organizers: Pia Sommerauer, Tommaso Caselli, Malvina Nissim, Levi Remijnse, Piek Vossen

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[CFP] REPL4NLP 2024: First Call for Papers
by Pepa Atanasova 08 Feb '24

08 Feb '24

Apologies for cross-posting. --------------------------------------------------------------------------- The *9th Workshop on Representation Learning for NLP (RepL4NLP 2024)*, co-located with ACL 2024 in Bangkok, Thailand, invites papers of a theoretical or experimental nature describing recent advances in vector space models of meaning, compositionality, and the application of deep neural networks and spectral methods to NLP. We welcome submissions on representations of text, as well as representations that are multi-modal, cross-lingual, representations of symbolic languages, code, enriched with external knowledge, or structure-informed (syntax, morphology, etc). *Topics for the workshop will include, but are not limited to:* - *Developing new representations*: at any level of granularity (document to character) using supervised, unsupervised or semi-supervised techniques for a multitude of tasks such as language modeling, similarity search, clustering, etc. - *Efficient learning of representations*: with respect to training and inference time, model size, amount of training data, etc. - *Evaluating representations*: with respect to training objectives (for LLMs: next token prediction, RLHF, span-mask denoising, etc), types of test data (e.g., text vs code), and architectures (decoder-only, encoder-decoder, etc), as well as assessing representations for generalization, compositionality, and robustness (e.g., adversarial), etc. - *Representation analysis*: methods for visualizing, explaining, and inspecting specific properties of representations (e.g., through probing), enhancing their interpretability, investigating their influence on the model's behavior, assessing the causal impact of interventions within the representation space on the model's behavior, etc. - *Relating representation to behavior*: whether, and to what extent, a model’s representations cause, condition, or boost its behavior (e.g., for LLMs: the relationship between encoded knowledge and task performance). Is possessing good representations necessary or sufficient for solving a task? Vice versa, is model behavior informative of its learned representations? *Key Dates* Direct paper submission deadline: May 17, 2024 ARR commitment deadline: June 1, 2024 Notification of acceptance: June 17, 2024 Camera-ready papers due: July 1, 2024 Workshop date: Aug 16, 2024 *Submissions*Papers may be long (maximum 8 pages plus references) or short (maximum 4 pages plus references). We encourage authors to include a broader impact and ethical concerns statement, following ARR Ethics Policy from the main conference. Papers can be submitted directly via OpenReview. *ACL 2023 fast-track submissions*Papers submitted to the ACL 2024 main conference that have not been selected can be submitted to the RepL4NLP 2024 fast-track. We will then make a decision based on your reviews received from ACL 2024. Note that you do not need to submit the reviews received from ACL 2024. *Website* https://sites.google.com/view/repl4nlp2024/ *Organizers* Chen Zhao, New York University Shanghai Marius Mosbach, Saarland University Pepa Atanasova, University of Copenhagen Seraphina Goldfarb-Tarrent, Cohere Peter Hase, University of North Carolina at Chapel Hill Arian Hosseini, University of Montreal Maha Elbayad, Meta AI Sandro Pezzelle, University of Amsterdam Maximilian Mozes, University College London

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Invitation: Panels on AI, LLM, NLP, Data Analytics and Social computing
by Wajdi Zaghouani 08 Feb '24

08 Feb '24

Dear colleagues I would like to invite you to register and join us *online *or ** in person ** in Qatar Foundation Minaretein building Auditorium on Feb 19th 2024 as of 9AM to attend two panels related to Data sciences, AI, LLM, NLP and Social computing to discuss topics such as Hate Speech Detection, Fake news Detection and Text analytics with an impressive lineup of International speakers such as *Dr. Kareem Darwish *(AIXPLAIN), *Dr. Kiran Garimella* (Rutgers University), Tuğrulcan Elmas ( University of Edinburgh), Roy Lee Ka Wei (Singapore University of Technology and Design) , Patrick Juola (Duquesne University), Jiří Milička (Charles University) and David Kaufer (Carnegie Mellon University). I believe this public event will be useful for faculty, students, researchers, staff etc. Please feel free to forward this invitation to your colleagues and students. The event is organized within the second HBKU MIDDLE EAST CONFERENCE 2024 Gender, Technology, and Digital Cultures in the Middle East Registration link (Free Registration) https://app.micetribe.com/public/workspaces/chss/events/1282251051/forms/vi… <https://eur05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fapp.micet…> Full Program (Feb 18 and Feb 19) https://www.hbku.edu.qa/en/mec2024/program <https://eur05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.hbku.…> Best, Wajdi Zaghouani ---- *Wajdi Zaghouani, Ph.D.* *Associate Professor in Digital Humanities* College of Humanities and Social Sciences P.O. Box 34110 | Education City | Doha, Qatar tel: +974 4454 5601 | mob: +974 33454992 wzaghouani(a)hbku.edu.qa| Office A141, LAS Building

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[CFP] Special issue on Abusive Language Detection of the journal Traitement Automatique des Langues (TAL)
by farah benamara 08 Feb '24

08 Feb '24

================[Apologies for any cross-posting]================ **Special issue of the journal Traitement Automatique des Langues (TAL) Abusive Language Detection : Linguistic Resources, Methods and Applications ** **Guest Editors** Farah Benamara (IRIT-Toulouse University, IPAL Singapore), Delphine Battistelli (MoDyCo, Paris Nanterre University) and Viviana Patti (Turin University) **Motivations** Abusive language - or, in another very common terminology, hate speech - and the propagation of harmful stereotypes have unfortunately become commonplace occurrences on various social media platforms, partly due to users’ freedom and anonymity and the lack of regulation provided by these platforms. The sheer volume and often implicit nature of such unwanted content make manual moderation of these user spaces a formidable task. Various scientific communities interested in its at least partial automation have taken up the problem over the past ten years. In particular, Computational Social Science, Natural Language Processing and Computational Linguistics have proposed numerous works to create resources, datasets, and models aimed at automating the task of abusive language detection (henceforth ALD). In fact, we see that ALD has become a research theme in its own right in the field of Natural Language Processing with an abundant literature. Abusive language (umbrella term to refer to the various forms of harmful language, such as toxic, offensive language, hate speech, and stereotypes) is topically focused and each specific manifestation of abusive language targets different vulnerable groups based on characteristics such as gender (misogyny, sexism), ethnicity, race, religion (xenophobia, racism, Islamophobia), sexual orientation (homophobia), and so on. Most automatic ALD approaches cast the problem into a binary classification task but important considerations should be taken into account, in particular: (1) the topical focus or the target-oriented nature of hate speech ; (2) the degree of engagement of users in abusive content (e.g., denunciation, approbation, reporting, neutral attitude) ; (3) the question of stereotypes and dominant ideologies ; (4) the question of linguistic strategies more particularly linked or born with social networks (e.g., emoticons, hashtags). Furthermore, most of the work (resources, classifiers) is developed for English. **Topics** Motivated by the interest of the community in the problem of ALD, we invite papers from Natural Language Processing, Machine Learning and Computational Social Sciences. We explicitly encourage interdisciplinary submissions (resources, computational methods, and user applications at the interface of linguistics/psychology/socio-linguistics/sociology) but also position papers on the actual state of the art in the field discussing the limitations of the current approaches and directions for future work. The topics covered by the special issue include, but are not limited to: -- Linguistic resources and evaluation: annotation schemes, corpus linguistics studies, new datasets, with a particular interest in French language and/or multilingual resources. In the case of strictly lexical resources: methods for constituting them and coverage, semantic categories retained. -- Formal/Conceptual approaches for ALD as inspired by models in sociology, socio-linguistics and psychology. -- Models and Methods: supervised and unsupervised approaches, including LLMs. -- Role of contextual phenomena, including discourses, extra-linguistic contexts (e.g., cultural aspects). -- Models for cross-lingual and multimodal detection. -- New approaches beyond binary classification: target-oriented ALD, degrees of user engagement, etc. -- Dynamics of online AL in social media, propaganda propagation. -- Bias detection and removal in resource creation, datasets and methods. -- Application of ALD tools in education, social media content moderation, etc. -- Social, legal, and ethical implications of detecting, monitoring and moderating AL. **Important dates** May 31th, 2024: Submission deadline July 15th, 2024: Notification of acceptance after first rereading End of September 2024: Revised version Mid October 2024: Final decision End of November 2024: Camera ready January 2025: Publication of the special issue **Submission** Submissions can either be in French or English and should follow the journal templates: https://tal-65-3.sciencesconf.org/ **About the journal** Traitement Automatiques des Langues Journal (TAL) is the international French journal of Natural Language Processing (https://www.atala.org/revuetal) published by ATALA (French Association for Natural Language Processing, http://www.atala.org) since 1959 with the support of CNRS (National Centre for Scientific Research). It is indexed by ACL Anthology as well as DBLP. It is also supported by the Institute of Human and Social Sciences of the CNRS. **Contact** For any question, please contact tal-65-3(a)sciencesconf.org **External committee** -- Cristina Bosco, University of Turin -- Elena Cabrio, University of Côte d'Azur -- Tommaso Caselli, Faculty of Arts, Rijksuniveristeit Groningen -- Valentina Dragos, ONERA -- Karën Fort, Sorbonne University -- Claire Hugonnier, University of Grenoble Alpes -- Irina Illina, University of Lorraine -- Roy Ka-Wei Lee, Singapore University of Technology and Design -- Véronique Moriceau, IRIT, University of Toulouse -– Frédérique Segond, INRIA Paris -- Mariona Taulé, University of Barcelona -- Samuel Vernet, Aix-Marseille University -- Mathieu Valette, Paris Sorbonne Nouvelle University -- Marcos Zampieri, George Mason University -- ======================== Farah Benamara Zitoune Professor in Computer Science, Université Paul Sabatier IRIT-CNRS 118 Route de Narbonne, 31062, Toulouse. Tel : +33 5 61 55 77 06 http://www.irit.fr/~Farah.Benamara ==================================

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12th International Conference and Workshops on Technology and Chinese Language Teaching
by bbs lists 07 Feb '24

07 Feb '24

Call for papers: 12th International Conference and Workshops on Technology and Chinese Language Teaching (TCLT12), June 22 to 23, 202, University of California, Los Angeles. Conference will be held online. More information about the conference can be found from the conference website.: http://www.tclt.us/tclt12/cfp.php

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