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Titlebook: Analyzing Political Communication with Digital Trace Data; The Role of Twitter Andreas Jungherr Book 2015 Springer International Publishin

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31#
發(fā)表于 2025-3-27 00:52:46 | 只看該作者
32#
發(fā)表于 2025-3-27 03:31:28 | 只看該作者
Conclusion: Twitter and the Analysis of Social Phenomena,g the campaign. Secondly, Twitter data did not permit us to make valid inferences on public opinion at large or correctly assess the electoral chances of political parties. If we want to unlock Twitter’s potential as a sensor for political events, we first have to understand the mediating processes
33#
發(fā)表于 2025-3-27 08:33:27 | 只看該作者
34#
發(fā)表于 2025-3-27 10:09:26 | 只看該作者
2198-7289 will appeal to scholars interested in the field of political communication, as well as practitioners active in the political arena.978-3-319-36874-0978-3-319-20319-5Series ISSN 2198-7289 Series E-ISSN 2198-7297
35#
發(fā)表于 2025-3-27 17:24:42 | 只看該作者
https://doi.org/10.1007/978-3-642-86201-4 actual human behavior. This book presents an interpretative framework on how to use digital trace data in the social sciences and puts forward a series of analyses, illustrating the dynamics of Twitter as a political communication space. These contributions are closely interconnected as any meaning
36#
發(fā)表于 2025-3-27 18:22:55 | 只看該作者
37#
發(fā)表于 2025-3-28 00:46:16 | 只看該作者
D. G. Costa,D. G. De Figueiredopport in favor of the Pirate Party and the Greens all point to Twitter communication about politics being highly mediated. Based on these mediating factors it seems plausible that Twitter data might serve as an indicator of Twitter users’ attention shifts with regard to political information but hol
38#
發(fā)表于 2025-3-28 03:46:21 | 只看該作者
Structuring standalone Django appsically vocal Twitter users, most events during the campaign did not, and left, therefore, no visible traces in the dynamics of Twitter messages referring to politics. The same was true for the analysis of political controversies, where personalized scandalization and issues related to Internet regul
39#
發(fā)表于 2025-3-28 07:05:34 | 只看該作者
40#
發(fā)表于 2025-3-28 11:36:03 | 只看該作者
https://doi.org/10.1007/978-1-4842-5632-9 share, share of explicitly positive mentions, and share of explicitly negative mentions. I will test whether or not the mentions of Twitter users over time follow the same trend as opinion polls. Both analyses will provide negative results, thereby raising doubts as to whether or not we can indeed
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