A manifesto for data sharing in social media research

Abstract

"More and more researchers want to share research data collected from social media to allow for reproducibility and comparability of results. With this paper we want to encourage them to pursue this aim - despite initial obstacles that they may face. Sharing can occur in various, more or less formal ways. We provide background information that allows researchers to make a decision about whether, how and where to share depending on their specific situation (data, platform, targeted user group, research topic etc.). Ethical, legal and methodological considerations are important for making this decision. Based on these three dimensions we develop a framework for social media sharing that can act as a first set of guidelines to help social media researchers make practical decisions for their own projects. In the long run, different stakeholders should join forces to enable better practices for data sharing for social media researchers. This paper is intended as our call to action for the broader research community to advance current practices of data sharing in the future." (author's abstract

Detection and Resolution of Rumours in Social Media

“…These tend to change frequently and hence it is recommended to check them before releasing a dataset. Often, releasing raw data is not permitted and is limited to the unique identifiers of the content, e.g., tweet IDs; users must then use the IDs to collect raw the data themselves (Weller and Kinder-Kurlanda 2016). There are exceptions, however; Twitter, for instance, allows researchers to release small datasets of up to 50,000 tweets, including raw data.…”

A longitudinal assessment of the persistence of twitter datasets

“…With the increasing use of social media data for research purposes (Kaplan & Haenlein, ), the concerns for making sure that datasets used in these works are released are growing (Weller & Kinder‐Kurlanda, ). Sharing data is crucial for many reasons, including the ability to reproduce results from existing research, as well as to extend existing work with new analyses and findings by using common datasets (Borgman, ).…”

“…In recent years, the use of large‐scale datasets for research has increased with the emergence of the Web and social media (Ruths & Pfeffer, ; Tufekci, ; Kjellberg, Haider, & Sundin, ). Despite the increasing interest in sharing social media datasets (Wallis, Rolando, & Borgman, ; Stvilia et al, ), there is also concern about the persistence of these data (Weller & Kinder‐Kurlanda, ). The long‐term persistence of datasets can be impeded by different circumstances.…”

“…Another important reason is that datasets gathered from third party services, such as social media data (Chinthakayala, Zhao, Kong, & Zhang, ; Hutton & Henderson, 2015a, 2015b; Metaxas & Mustafaraj, ), cannot always be shared in its final form owing to restrictions in the terms and conditions of the data provider. To circumvent these restrictions, researchers can share unique identifiers of individual posts, which then enable recollection of the data, as is the case with Twitter; recollecting social media datasets from unique identifiers, however, leads to the collection of a dataset that differs from the original, as part of the data may no longer be available (McCreadie et al, ; Weller & Kinder‐Kurlanda, ), for example, because user accounts may have been deleted or suspended (Liu, Kliman‐Silver, & Mislove, ). Moreover, the metadata of social media posts can also change over time as their authors update their profile, their number of followers or friends keeps changing and/or the number of shares/likes of posts is altered (Holsapple, Hsiao, & Pakath, ).…”

Big Data & New Data: Ein Ausblick auf die Herausforderungen im Umgang mit Social-Media-Inhalten als neue Art von Forschungsdaten

“…Archivierte Datensätze, die bereits auf Einhaltung ethischer Standards geprüft wurden, könnten dann wiederum für andere Forschende zugänglich gemacht werden, die somit nicht ihrerseits von vorne mit diesbezüglichen Überlegungen beginnen müssten. Allgemein wären Fortschritte im Bereich der Datenarchivierung von Social-Media-Daten äußerst wünschenswert(Weller/Kinder-Kurlanda 2016). Sie könnten dabei helfen, den Datenzugang insgesamt zu erleichtern und damit ggf.…”