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How much time do you spend online? Understanding and improving the accuracy of self-reported measures of internet use Araujo, T.B.; Wonneberger, A.; Neijens, P.C.; de Vreese, C.H. : 10.1080/19312458.2017.1317337 Link to publication Published in: Communication Methods and Measures DOI Citation for published version (APA):Araujo, T., Wonneberger, A., Neijens, P., & de Vreese, C. (2017). How much time do you spend online? Understanding and improving the accuracy of self-reported measures of internet use. Communication Methods and Measures, 11(3), 173-190. DOI: 10.1080173-190. DOI: 10. /19312458.2017 General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Given the importance of survey measures of online media use for communication research, it is crucial to assess and improve their quality, in particular because the increasingly fragmented and ubiquitous usage of internet complicates the accuracy of self-reported measures. This study contributes to the discussion regarding the accuracy of self-reported internet use by presenting relevant factors potentially affecting biases of self-reports and testing survey design strategies to improve accuracy. Combining automatic tracking data and survey data from the same participants (N = 690) confirmed low levels of accuracy and tendencies of over-reporting. The analysis revealed biases due to a range of factors associated with the intensity of (actual) internet usage, propensity to multitask, day of reference, and the usage of mobile devices. An anchoring technique could not be proved to reduce inaccuracies of reporting behavior. Several recommendations for research practice follow from these findings.

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Issue arenas, as places for societal discussions, have recently been studied as an important aspect of organizational environments. While a fundamental part of any issue arena is the distinction between active and passive actors, empirical analyses have mainly focused on active stakeholders. We approach issue arenas as communication networks in which active stakeholders discuss topics and involve passive stakeholders. Based on network theory, we introduce an automated method for mapping these issue arenas on Twitter. In particular, we combine manual coding of active stakeholders, and automated semantic network analysis of addressed, passive stakeholders and their topics of discussion. Empirically, we focus on the issue of bird flu affecting poultry farming in the Netherlands from 2015 to 2017 with a sample of 704 Twitter messages. Instead of pre-defining a set of stakeholders for the analysis, our approach to study communication networks in online settings allows for mapping issue arenas based on the stakeholders that communicate about the topic.

Although Facebook provides organizations with the opportunity to easily engage with stakeholders online, very little is known about the effectiveness of organizational communication strategies. This study examines how nonprofit organizations (NPOs) use Facebook to engage with stakeholders through stakeholder dialogic strategies and relational maintenance strategies with the goal of fostering stakeholder relationship growth and obtaining social legitimacy.

Social media platforms provide major opportunities for online activism and the emergence of digital counterpublics. Research on counterpublics has focused on actors and their narrative strategies aiming at deconstructing dominant discourses. Less attention has been paid to how the interplay between actors and platformspecific functions affects the configurations and therewith also the success of digital counterpublics. Existing studies mainly rely on determining up front which topics, actor characteristics, or arguments constitute hashtag activism and digital counterpublics. In contrast, our approach allows for an empirical identification based on how actors position themselves in an online debate toward other actors and their shared hashtags. We argue that online activism is co-constituted by actors and their usage of hashtags, actor mentions, and retweets. Applying a communicative network perspective allows for the integration of semantic and relational research traditions. We combine a recently developed automated network analysis method and content analysis to analyze two Twitter debates about animal welfare issues. Our results show that among Twitter users, citizens and environmental organizations formed a common cluster whereas media actors formed their own sub-clusters in both debates. The findings emphasize the central role of citizens for the configuration of digital counterpublics. The proposed approach can be further adapted and applied more widely for the analysis of online activism and debates.

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