A Decade of News Forum Interactions: Threaded Conversations, Signed Votes, and Topical Tags

TL;DR

This paper introduces a comprehensive, anonymized, ten-year dataset of online discussions from DerStandard, enabling advanced research on discourse dynamics, user interactions, and topical analysis in German media.

Contribution

It provides a large-scale, longitudinal, anonymized dataset with detailed interaction metadata and semantic representations, facilitating diverse computational social science research.

Findings

Rich insights into online discussion patterns

Effective anonymization preserving data utility

Support for multilingual and semantic analyses

Abstract

We present a large-scale, longitudinal dataset capturing user activity on the online platform of DerStandard, a major Austrian newspaper. The dataset spans ten years (2013-2022) and includes over 75 million user comments, more than 400 million votes, and detailed metadata on articles and user interactions. It provides structured conversation threads, explicit up- and downvotes of user comments and editorial topic labels, enabling rich analyses of online discourse while preserving user privacy. To ensure this privacy, all persistent identifiers are anonymized using salted hash functions, and the raw comment texts are not publicly shared. Instead, we release pre-computed vector representations derived from a state-of-the-art embedding model. The dataset supports research on discussion dynamics, network structures, and semantic analyses in the mid-resourced language German, offering a reusable resource across computational social science and related fields.