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Crowd employment is a new form of short-term and flexible employment that has emerged during the past decade. To understand this new form of employment, it is crucial to illuminate the underlying motivations of the workforce involved in it. This article introduces the Multidimensional Crowdworker Motivation Scale (MCMS), a scale for measuring the motivation of crowdworkers on microtask platforms. The MCMS is theoretically grounded in self-determination theory and tailored specifically to the context of paid crowdsourced microlabor. The scale measures the motivation of crowdworkers along six motivational dimensions, ranging from amotivation to intrinsic motivation. We validated the MCMS on data collected in ten countries and three income groups. Factor analyses demonstrated that the MCMS's six dimensions showed good model fit, validity, and reliability. Furthermore, our measurement invariance tests showed that motivations measured with the MCMS are comparable across countries and income groups, and we present a first cross-country comparison of crowdworker motivations. This work constitutes an important first step toward understanding the motivations of the international crowd workforce.

"Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a discussion of theoretical constructs in sociological theory. The resulting measures make different - mostly qualitative - aspects of online conversational practices amenable to computation. We evaluate our computational approach by applying it in a case study. In particular, we study online conversational practices of German politicians on Twitter during the German federal election 2013. We find that political parties share some interesting patterns of behavior, but also exhibit some unique and interesting idiosyncrasies. Our work sheds light on (i) how complex cultural phenomena such as online conversational practices are amenable to quantification and (ii) the way social media such as Twitter are utilized by political parties." (author's abstract)

Web 2.0 platforms have become a ubiquitous way of information exchange, but are seldom integrated with the Web of Data. To overcome this situation
we propose the usage of SKOS thesauri acting as back-of-the-book index providing domain-specific axes transcending applications. We illustrate this
concept with a use-case in the social sciences domain but applications in other domains are possible. (author's abstract)

Social Media Monitoring des Bundestagswahlkampfs 2017

Dieser Datensatz enthält Ergebnisse aus dem Social Media Monitoring von Facebook und Twitter für den Bundestagswahlkampf 2017. Das Projekt sammelte die Tweets und Facebook-Posts von politischen Kandidaten und Organisationen und das Engagement der Nutzer mit diesen Inhalten - Retweets und @-Mentions auf Twitter, Kommentare, Shares und Ähnliches auf Facebook. Schließlich wurden alle Nachrichten auf Twitter gesammelt, die mindestens ein Schlüsselwort zu zentralen politischen Themen enthalten. Alle Daten waren zum Zeitpunkt der Datenerhebung öffentlich zugänglich. Die gesammelten Daten sind Eigentum von Facebook und Twitter. Aus diesem Grund und im Hinblick auf die Datenschutzbestimmungen können nur die folgenden Aspekte der Daten weitergegeben werden:

(1) Eine Liste aller Kandidaten, die im Projekt berücksichtigt wurden, ihre Schlüsselattribute und die Identifikation ihrer jeweiligen Twitter-Accounts und Facebook-Seiten.

Kandidatendatensatz: Vor- und Nachname des Kandidaten, akademischer Titel und Namenszusatz falls vorhanden; URL des ersten Facebook-Accounts; URL des zweiten Facebook-Accounts; URL des Twitter-Accounts; Kandidat ist auf einer Parteiliste gelistet; Listenplatz; Direktkandidat in einem der Wahlkreise; Wahlkreisnummer; Name des Wahlkreises; Bundesland; Kandidat ist Mitglied des Bundestages; Parteizugehörigkeit; Geschlecht; Alter (Geburtsjahr); Wohnort; Geburtsort; Beruf.
Zusätzlich verkodet wurde: Eindeutige ID.

(2) Listen von Organisationen, die während eines Wahlkampfes relevant sind, d.h. politische Parteien und wichtige Gatekeeper, mit ihren jeweiligen Twitter- und Facebook-Accounts.

(3) Eine Liste von Tweet-IDs, die verwendet werden können, um die Tweets abzurufen, die wir während unseres Forschungszeitraums gesammelt haben.

As more and more people use social media to communicate their view and perception of elections,
researchers have increasingly been collecting and analyzing data from social media platforms.
Our research focuses on social media communication related to the 2013 election of the
German parliament [translation: Bundestagswahl 2013]. We constructed several social media
datasets using data from Facebook and Twitter. First, we identified the most relevant candidates
(n=2,346) and checked whether they maintained social media accounts. The Facebook data was
collected in November 2013 for the period of January 2009 to October 2013. On Facebook we
identified 1,408 Facebook walls containing approximately 469,000 posts. Twitter data was collected
between June and December 2013 finishing with the constitution of the government. On
Twitter we identified 1,009 candidates and 76 other agents, for example, journalists. We estimated
the number of relevant tweets to exceed eight million for the period from July 27 to September
27 alone. In this document we summarize past research in the literature, discuss possibilities
for research with our data set, explain the data collection procedures, and provide a description
of the data and a discussion of issues for archiving and dissemination of social media data.