Call for participants
Distant reading, digital methods, computational social sciences, and statistical learning from textual data are general terms that refer to a wide range of methods that have a common aim: retrieving information from texts using computer-aided tools. Today, computer-aided text analysis is an umbrella term referring to a number of qualitative, quantitative and mixed-methods approaches. It is an object of research in many sectors of linguistics, computer sciences, mathematics and statistics. Furthermore, computer-aided text analysis is used as a research tool within many disciplines such as psychology, philosophy, sociology, sociolinguistics, education, history, political studies, literary studies, communication and media studies. The recent evolution of information technologies (IT) and computational methods has led to several distinct but interrelated sectors (e.g. computational linguistics, information retrieval, natural language processing, text mining, text analytics, sentiment analysis, opinion mining, topic extraction, etc.) with interesting industrial applications, such as media and new media monitoring, electronic dictionaries and translators, plagiarism detection and similar.
Recent developments in digital methods are not only changing how research is conducted in the humanities and social sciences, but also how new research is planned and designed. The interest in news collections arose with the investigation of propaganda in press coverage during the first half of the 20th century. Today, large corpora of texts and text mining tools are exploited to extract hot topics, sentiment, opinions and trends.
The IQLA-GIAT Summer School is characterized by three main elements:
- a general part devoted to quantitative methods;
- a special issue addressed to a relevant methodological problem that has changed over time
2021: Quality of Texts quality of News
2019: Data Science and Data scientists in Humanities and Social Sciences;
2017: Topic detection and authorship attribution in Elena Ferrante’s case-study;
2015: Measuring style and computational stylistics;
2013: Measures and methods in authorship attribution
- lab-tutorials dedicated to the computer-aided analysis of textual data.
Teaching activities at the School will raise questions that can be answered thanks to quantitative methods implemented within a text analysis framework and other procedures that may be used to identify and compare text characteristics. The aim is to discuss the strengths, weaknesses, opportunities and threats of quantitative methods for text analysis with postgraduate students, early career researchers and scholars of different disciplines.
Recent studies have stressed the need for developing, adopting and sharing interdisciplinary approaches. The IQLA-GIAT Summer School is an ideal environment for developing innovative analytical tools by pooling together the research methods from different disciplines.
The Summer School aims at:
- sharing information on software, corpora, relevant literature and research results;
- promoting dialogue among different disciplines on emerging research issues;
- developing innovative analytical tools and integrated research methods;
- introducing postgraduate students and early career researchers to new strains of research and applications;
- sharing state-of-the-art techniques in methods for text analysis (topic detection, text classification, data visualization).
===Does this School fit your needs?===
Would you like to consider a large number of relevant articles published by newspapers, novels, transcriptions of open-ended interviews, or comments posted on social media in your research? Are there definitely too many texts for any scholar to read them in a life span?
Why not trying to ask a computer to do this task?
A software package is not able to close read a text. On the contrary, using mathematical and statistical tools might be smart to distant read a text (i.e., collecting data, retrieving relevant information, summarizing features, finding patterns, etc.). Instead of close-reading a limited number of texts, why not working with thousands of texts, upload them into the memory of a computer and ask a software package to produce analyses and results?
===Application and deadlines===
The IQLA-GIAT Summer School is open to 30 participants including researchers, scholars and postgraduate students. The limited number of 30 participants is meant to foster an effective online interaction among participants and between participants and lecturers.
Applicants should send a file in pdf format including:
- curriculum vitae;
- personal mission statement and research interests (max 500 words);
Applications should be sent to the following address: qatd.school at fisppa.it
Please note that this year there is no selection procedure and that the limited seats will be sold on a “first-come, first-served” basis. Deadline July, 15th
The first 30 applicants will receive information to complete their registration with the payment of the tuition fee. Tuition fee 150 €
The 5th edition of the IQLA-GIAT Summer School is an online event. It will take place via the Zoom platform from Monday 26th to Friday 30th July 2021.
The IQLA-GIAT Summer School is a full-time intensive course.
On Friday, the last two hours will be left for the final assessment.
The IQLA-GIAT Summer School in Quantitative Analysis of Textual Data is organized by GIAT – Interdisciplinary Text Analysis Group (www.giat.org) in collaboration with the International Quantitative Linguistics Association (www.iqla.org).
The IQLA-GIAT Summer School is a project funded by the University of Padova (www.unipd.it) and coordinated by Professor Arjuna Tuzzi (University of Padova).
The School is managed by the Department of Philosophy, Sociology, Education & Applied Psychology – University of Padova (Italy).
All courses are in English. Teaching activities include lectures, tutorials, as well as Q&A sessions. The teaching staff includes researchers and experts from different Universities and Research institutes:
- Dominique Brunato, ILC-CNR, Italy
- Fabio Ciotti, Universitą di Roma Tor Vergata, Italy
- Maciej Eder, University of Kraków, Poland
- Ramon Ferrer-i-Cancho, Universitat Politčcnica de Catalunya, Spain
- Emmerich Kelih, University of Vienna, Austria
- Patrick Juola, Duquesne University, Pittsburgh, United States
- Georgios Mikros, HBKU, Doha, Qatar
- Stefano Ondelli, University of Trieste, Italy
- Pierre Ratinaud, Université Toulouse II, France
- Jan Rybicki, Jagiellonian University of Kraków, Poland
- Jacques Savoy, University of Neuchātel, Switzerland
- Floriana Sciumbata, University of Trieste, Italy
quantitative linguistics, computational stylistics, stylometry, syntactic analysis, texts and gender, texts and special needs, profiling, topic extraction, text classification
===Final Evaluation and self-assessment===
All participants will be requested to complete an evaluation questionnaire to express their opinions about the main aspects of the IQLA-GIAT Summer School (e.g., organization, teaching, materials, facilities and equipment, expectations, satisfaction rate, suggestions, etc.).
It is worth mentioning that the fifth edition of the Summer School is organized also considering the results and suggestions obtained through the evaluation questionnaires done in 2013, 2015, 2017, and 2019 editions.
All participants will complete a self-assessment questionnaire on technical skills and general knowledge including 30 multiple-choice questions (one correct answer out of four). Grades will reflect the sum of all correct answers (one point) according to the following range: A (29-30 points); B (25-28 points); C (21-24 points); D (17-20 points); E (15-16 points).
===Website and social networks===
The IQLA-GIAT Summer School will provide a specific website within GIAT’s domain (www.giat.org) for sharing learning resources, links and bibliographic references before, during and after the Summer School.
The IQLA-GIAT Summer School is also active on social networks:
For any further information and details about terms, deadlines, application forms and payment methods, please contact: qatd.school at fisppa.it
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