GESIS presents a diverse array of talks originating from the department “Knowledge Technologies for the Social Sciences.” These sessions delve into the development of research data infrastructures and technologies tailored for the social science community, with a primary focus on leveraging artificial intelligence to enhance accessibility to research data and information.
The exploration commences by delving into the information-seeking behavior and data requirements of social scientists. This foundational understanding serves as the bedrock for crafting suitable search infrastructures and knowledge graphs, ensuring that social science data and information become easily discoverable, accessible, and reusable. Progressing from this groundwork, we illuminate the opportunities and challenges arising from the integration of technological advancements in the social sciences, including the utilization of large language models and innovative data sources gleaned from the vast expanse of the Web
The conclusion of the series features an insightful presentation on the automatic extraction of scientific information from scholarly texts. This groundbreaking process contributes significantly to refining search mechanisms and enhancing comprehension of research information and their interdependencies.
Set up & registration: Each session consists of a talk and a moderated Q&A part. All talks will take place online as zoom-meetings on Thursdays, 1 pm-2 pm (CET/CEST). Please register for the session(s) you are interested in below. Your registration will be confirmed by email.
For more information click here.
15.02.2024 (THU), 13:00-14:00 (CET): Five Ways to Turn your Dataset into Click Bait
Slides | Presentation on YouTube | MTE Playlist
The Lecture will be held in English.
Finding suitable datasets is a difficult task. But why? In this talk, we will look at national and international efforts to increase findability, why they are important and what everyone can do to make their data better findable. This will include concrete advice to game the system and increase your data citation count.
Presenters:
14.03. 2024 (THU), 13:00-14:00 (CET): Searching the Social Sciences with GESIS Search
Registration (via Zoom) |
Slides | Presentation on YouTube | MTE Playlist
The Lecture will be held in English.
In the social sciences, research data and related information are often distributed on websites, search portals, data archives, and databases. In this talk, we present GESIS Search, which provides a central search entry point to the information space of empirical social science. Users can find national and international research data sets, publications, survey variables, questions from questionnaires, survey instruments, and tools. We will talk about how research information can be found in different categories, how information is linked and can be browsed, and what the future will bring for GESIS Search. This talk addresses researchers and interested parties looking for data and interested in specialized search environments.
Presenters:
11.04.2024 (THU), 13:00-14:00 (CET): How knowledge graphs can help you to share research data and information
Registration (via Zoom) |
Slides | Presentation on YouTube | MTE Playlist
The Lecture will be held in English.
Sharing research data and information has become a crucial demand for reusability, reproducibility, and visibility. The FAIR principles give recommendations on how to improve findability, accessibility, interoperability, and reusability. In this talk, we will present the basic concept of Knowledge Graphs and will show how they can support the sharing of research data and information in a FAIR way.
Presenters:
16.05.2024 (THU), 13:00-14:00 (CET): Opportunities and challanges of Large Language Models for the social sciences
Registration (via Zoom) |
Slides | Presentation on YouTube | MTE Playlist
The Lecture will be held in English.
Abstract will be available soon!
Presenters:
13.06.2024 (THU), 13:00-14:00 (CET): Preserving and Analysing Large-Scale Twitter Data
Registration (via Zoom) |
Slides | Presentation on YouTube | MTE Playlist
The Lecture will be held in English.
Preserving data from social media is crucial for many scientific disciplines. Publicly available social media archives facilitate research in the social sciences and provide corpora for training and testing a wide range of machine learning and natural language processing methods. To reduce the reliance on commercial gatekeepers, we decided in 2013 to create a large-scale longitudinal archive of tweets from X (then Twitter) for research purposes. We collected data from the then freely available random sample of 1% of all tweets from Twitter’s streaming API. In this talk, we will introduce TweetsKB – a knowledge base of tweets that has been enriched with named entities and sentiments. We also show how TweetsKB can be used to create topic specific sub-corpora, focusing on important societal events such as the COVID-19 pandemic. Understanding the COVID-19 discourse, its differences to the general Twitter discourse, and interdependencies with real-world events or (mis)information can foster valuable insights.
Presenters:
11.07.2024 (THU), 13:00-14:00 (CET): Introduction to Scholarly Information Extraction
Registration (via Zoom) |
Slides | Presentation on YouTube | MTE Playlist
The Lecture will be held in English.
Scholarly Information Extraction’ involves identifying resources, concepts, actors, and their relationships from scholarly documents and related data sources, such as software repositories. This forms the basis for many use cases, including automated literature reviews and advanced search applications. The talk presents the fundamental concepts and methodologies for scholarly information extraction, followed by a presentation of a scholarly information extraction project from start to finish.Scholarly Information Extraction’ involves identifying resources, concepts, actors, and their relationships from scholarly documents and related data sources, such as software repositories. This forms the basis for many use cases, including automated literature reviews and advanced search applications. The talk presents the fundamental concepts and methodologies for scholarly information extraction, followed by a presentation of a scholarly information extraction project from start to finish.
Presenters: