CSS SUMMER SCHOOL 2022:

Text mining and Natural Language Processing for Computational Social Sciences

We welcome applications to the 2nd SocialComQuant Summer School on Computational Social Science. This is the second Summer School of a series of 3 organized by the project SocialComQuant.

The second school of this series will focus on METHODS FOR ANALYZING AND MODELING TEXTUAL DATA (e.g. text mining, text classification, information extraction, sentiment analysis, latent semantic models, NLP, event extraction). 

The school will gather a number of diverse and outstanding speakers who will teach different methods and approaches to text mining, providing guidance through practical examples and coding exercises. 

Students will conduct small projects in which they will apply the newly learned methods, and the lecturers will supervise them.

IMPORTANT DATES


Application deadline: April 30, 2022 (23:59 AoE)

Notification: May 15, 2022 The results will be announced between  May 23-29, 2022.

School dates: July 25 - 29, 2022 

FORMAT


The School will take place at the Rumelifeneri Campus of Koç University, in Istanbul. Students are encouraged to join the Summer School in person, however, the School will allow students to join in hybrid mode. 

Some of the lecturers will be participating remotely and a limited number of slots will be reserved for remote participation by students.

COST


Participation in summer school comes with no fees.

Students are expected to cover their travel expenses. 

The Social Comquant Project will provide meals (breakfast, lunch, and dinner) during the Summer School at no cost.

Accommodation will be provided to all in-person participants if housing facilities will be made available by the university and government regulations regarding the Covid-19 pandemic. We will provide updates on this on a regular basis.

APPLY FOR PARTICIPATION


Please submit your motivation letter (one-page max), and CV in one single PDF file via EasyChair.

 

The school is open to anyone interested in learning about the use of text processing techniques for Computational Social Science.

Previous coding experience is not strictly required but students are encouraged to become familiar with a scripting language like Python or R before joining the summer school. 

The aim is to bring together a heterogeneous international group of people. However, we have a limited number of places for participants and everyone needs to apply via EasyChair by the deadline.

EASYCHAIR


The applicants should submit their application (CV + motivation letter) as a single PDF file using the button "submit paper", as it was a conference paper.

There will be one author (name and affiliation of the applicant).

The title, abstract, and keywords can be "Summer School application".

FREQUENTLY ASKED QUESTIONS

  • To submit your application, please click on the link provided on the webpage https://socialcomquant.ku.edu.tr/summer-school-2022/
  • Open an Easychair account for yourself.
  • Log in with your Easychair credentials. Then, submit your application as it was a conference paper.
  • You should submit your application (CV + motivation letter) as a single PDF file using the button "submit paper", as it was a conference paper.
  • There will be one author (name and affiliation of the applicant).
  • The title, abstract, and keywords can be "Summer School application".

The application is open to people from any level of seniority who would like to learn about text processing methods. Regardless of your seniority level, please pay attention to explaining yourself and your motivations clearly in your motivation letter.

You are expected to customize your motivation letter depending on the content of the summer school that you apply for.

In the motivation letter, you are expected to give concrete reasons showing your interest in the (such as a project or paper you are currently working on or planning to work on in the future, etc.).  Moreover, it will be for your advantage if you include your previous experiences related to computational social sciences, along with your future plans in the field.

We also expect to build an academic network composed of students and scholars of CSS through Social ComQuant project and its events. So, it will be a bonus if you briefly clarify why & how you want to be a part of this network.

  • There is no registration fee for the Social ComQuant Summer School.
  • Also, accommodation and meals are provided by the Project as well.
  • Participants only need to cover their own travel expenses.

Please do not send a Linkedin profile, which would indicate that you did not spare the time or attention necessary for the application.

Application results will ideally be announced through e-mail between  May 23-29, 2022.

Please send your questions to socialcomquant@ku.edu.tr .

LECTURERS

Dr. Malak Abdullah
Assistant Professor @Jordan University of Science and Technology
Dr. N. Gizem Bacaksizlar Turbic
Researcher @GESIS- Leibniz Institute for the Social Sciences
Dr. Arnim Bleier
Researcher @GESIS- Leibniz Institute for the Social Sciences
Dr. Ali Hürriyetoğlu
Researcher @KNAW Humanities Cluster
Dr. Ayşe Deniz Lokmanoğlu
Postdoctoral Fellow @Nortwestern University
Dr. Yelena Mejova
Senior Research Scientist @ISI Foundation
Dr. André Panisson
Principal Scientist @ CENTAI
Dr. Gözde Gül Sahin
Assistant Professor @Koç University

PROGRAM

LECTURE ROOM

Tower - 2nd Floor (located at the university center).

REGISTRATION: 

8am - 9am (@lecture room; please register before breakfast to collect your meal tickets)

LECTURES

Data Analysis and Visualization by Dr. N. Gizem Bacaksizlar Turbic.

Text Classification: Emotion Detection as a Case Study by Dr. Malak Abdullah.

Hands-on Introduction to ML with Scikit-learn by Dr. Arnim Bleier.

Network Theory Introduction and Analysis by Dr. Michele Tizzoni

Topic Modelling in R Studio by Dr. Ayşe Deniz Lokmanoğlu.

Towards "Fair" NLP Models: An Overview of Recent Bias Detection and Mitigation Strategies by Dr. Gözde Gül Şahin.

Text Representation Learning by Dr. André Panisson.

Applying NLP & ML for CSS: Case Studies in Public Health by Dr. Yelena Mejova.

Regular Expressions by Dr. Ali Hürriyetoğlu.

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