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This chapter describes the current state of the art in altmetrics research and practice. Altmetrics-evaluation methods of scholarly activities that serve as alternatives to citation-based metrics-are a relatively new but quickly growing area of research. For example, researchers are expecting that altmetrics that are based on social media data will reflect a broader public's perception of science and will provide timely reactions to new scientific findings. This chapter explains how altmetrics have emerged and how they are related to the academic use of social media. It also provides an overview of current altmetric tools and potential data sources for computing alternative metrics, such as blogs, Twitter, social bookmarking services, and Wikipedia. (HRK / Abstract übernommen).

The state of Twitter research in the social science domain is investigated based on a set of 25 highly cited papers, identified with the Scopus database out of 370 social science publications on social media research. The analysis shows how social media research in the social sciences has risen since 2007. The selected top cited papers are analyzed concerning their domains, the applied meth-ods and the underlying data in use. It is shown that different methods, both experimental and analytical are applied, and that some papers have started to combine different modes of analysis. The size of the datasets used for studying Twitter varies considerably across studies. Furthermore, central advantages of studying data collected from Twitter are pointed out and open challenges in working with these particular data are listed. Challenges include, for example, data access via the Twitter API or via third party tools, representativeness of datasets and sampling strategies and ethical issues. (author's abstract)

For the last few decades, the Internet continually has changed scholarly workflows across disciplines. It has affected how scholars search for publications, retrieve information and communicate and distribute their own research findings. Online communication and collaboration influences academic institutions as well as academic publishers, science journalists and students. Within this special issue, we focus on social media and its influence on academic practice. (auhtor's abstract)

Die elf Beiträge des vorliegenden Sammelbandes behandeln Grundlagen und Lösungen zu unterschiedlichen Themen des Forschungsdatenmanagements, wie etwa zu Datentypen und Lebenszyklen von Daten, zur systematischen Planung und Umsetzung des Forschungsdatenmanagements, zum Datenschutz und den aktuellen Rechtsnormen, zu Regeln der Datenorganisation und zu den Abläufen in der Datenaufbereitung, zum Data Sharing sowie zur Sekundäranalyse von Forschungsdaten. Darauf aufbauend werden in weiteren Beiträgen die Anwendung von Metadaten sowie die Zitation von Forschungsdaten thematisiert. Aktuelle Herausforderungen beim Umgang mit 'neuen' Datentypen werden abschließend anhand von Social-Media- und Geo-Daten beispielhaft erörtert. Die dabei vorgestellten Konzepte und Maßnahmen bieten ein wichtiges Handwerkszeug für Sozialwissenschaftlerinnen und Sozialwissenschaftler und ihre Forschungsprojekte

Die elf Beiträge des vorliegenden Sammelbandes behandeln Grundlagen und Lösungen zu unterschiedlichen Themen des Forschungsdatenmanagements, wie etwa zu Datentypen und Lebenszyklen von Daten, zur systematischen Planung und Umsetzung des Forschungsdatenmanagements, zum Datenschutz und den aktuellen Rechtsnormen, zu Regeln der Datenorganisation und zu den Abläufen in der Datenaufbereitung, zum Data Sharing sowie zur Sekundäranalyse von Forschungsdaten. Darauf aufbauend werden in weiteren Beiträgen die Anwendung von Metadaten sowie die Zitation von Forschungsdaten thematisiert. Aktuelle Herausforderungen beim Umgang mit 'neuen' Datentypen werden abschließend anhand von Social- Media- und Geo-Daten beispielhaft erörtert. Die dabei vorgestellten Konzepte und Maßnahmen bieten ein wichtiges Handwerkszeug für Sozialwissenschaftlerinnen und Sozialwissenschaftler und ihre Forschungsprojekte.

The book is based on practical requirements for the management of quantitative research data in small to medium-sized research projects in the social sciences, which generate and analyse data, save original data and archive and make them available for further use in the long term. In order to equip scientists with the tools to specifically meet these requirements, typical questions of data-based research projects are addressed on the basis of application cases and systematically processed with proven concepts of research data management. Overall, the book is a practical guide to documenting data-based research products (e.g. data files, measuring instruments, survey methods, analysis syntaxes) step by step, securing them professionally and making them available for subsequent use. In addition, the book highlights open questions and current challenges in dealing with research data. In the interest of scientifically and methodologically sound research data management, it also opens up perspectives for university education and research into the management of research data.

It might still sound strange to dedicate an entire ebook exclusively to a single Internet platform. But it is not the company Twitter, Inc. that is the focus; this ebook is not about a platform and its features and services. It is about its users and the ways in which they interact with one another via the platform, about the situations that motivate people to share their thoughts publicly, using Twitter as a means to reach out to one another. And it is about the digital traces people leave behind when interacting with Twitter, and most of all about the ways in which these traces - as a new ty

This perspective article suggests considering the everyday research data management work required to accomplish social media research along different phases in a data lifecycle to inform the ongoing discussion of social media research data's quality and validity. Our perspective is informed by practical experience of archiving social media data, by results from a series of qualitative interviews with social media researchers, as well as by recent literature in the field. We emphasize how social media researchers are entangled in complexities between social media platform providers, social media users, other actors, as well as legal and ethical frameworks, that all affect their everyday research practices. Research design decisions are made iteratively at different stages, involving many decisions that may potentially impact the quality of research. We show that these decisions are often hidden, but that making them visible allows us to better understand what drives social media research into specific directions. Consequently, we argue that untangling and documenting choices during the research lifecycle, especially when researchers pursue specific approaches and may have actively decided against others (often due to external factors) is necessary and will help to spot and address structural challenges in the social media research ecosystem that go beyond critiques of individual opportunistic approaches to easily accessible data.

Online privacy research considers the determinants, dimensions, and consequences of information disclosure on the internet. In this endeavor, researchers often are interested in uncovering personal and potentially sensitive details about media use and (privacy-related) attitudes and behavior. This focus raises a number of ethical questions that researchers need to address. Ethical questions relate to issues of data protection, but also to other topics, such as the role of study participants. Digital trace data have become increasingly popular in the social and behavioral sciences in recent years and constitute a promising resource for online privacy research. While digital trace data come with their own set of challenges that may increase specific ethical concerns, they also hold the potential for innovation in research design, for the involvement of study participants, and for more research transparency. In this chapter, we discuss ethical challenges in online privacy research, with a particular focus on the role of participants, and illustrate how digital trace data – and their combination with other types of data – can be used to find and develop novel approaches for online privacy research that also consider key ethical questions.

With this work, we present a publicly available data set of the history of all the references (more than 55 million) ever used in the English Wikipedia until June 2019. We have applied a new method for identifying and monitoring references in Wikipedia, so that for each reference we can provide data about associated actions: creation, modifications, deletions, and reinsertions. The high accuracy of this method and the resulting data set was confirmed via a comprehensive crowdworker labeling campaign. We use the data set to study the temporal evolution of Wikipedia references as well as users' editing behavior. We find evidence of a mostly productive and continuous effort to improve the quality of references: There is a persistent increase of reference and document identifiers (DOI, PubMedID, PMC, ISBN, ISSN, ArXiv ID) and most of the reference curation work is done by registered humans (not bots or anonymous editors). We conclude that the evolution of Wikipedia references, including the dynamics of the community processes that tend to them, should be leveraged in the design of relevance indexes for altmetrics, and our data set can be pivotal for such an effort.