PUMA publications for /tag/media%20socialhttps://puma.ub.uni-stuttgart.de/tag/media%20socialPUMA RSS feed for /tag/media%20social2024-03-29T02:28:10+01:00Deepfakes: Technikfolgen und Regulierungsfragen aus ethischer und sozialwissenschaftlicher Perspektivehttps://puma.ub.uni-stuttgart.de/bibtex/2dd23bc272bcb336e6d373ddaaaf7b7a2/droesslerdroessler2022-03-25T13:06:25+01:00deepfakes ethik media medien politik projekt social soziale tango technik <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Pawelec" itemprop="url" href="/person/1e579507d9324b4a22449f6040a09f8ce/author/0"><span itemprop="name">M. Pawelec</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Cora Bieß" itemprop="url" href="/person/1e579507d9324b4a22449f6040a09f8ce/author/1"><span itemprop="name">C. Bieß</span></a></span></span>. </span><span class="additional-entrytype-information"><em><span itemprop="publisher">Nomos Verlagsgesellschaft mbH & Co. KG</span>, </em><em>Baden-Baden, </em>(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Fri Mar 25 13:06:25 CET 2022Baden-BadenKommunikations- und MedienethikDeepfakes: Technikfolgen und Regulierungsfragen aus ethischer und sozialwissenschaftlicher Perspektive162021deepfakes ethik media medien politik projekt social soziale tango technik Deepfakes – manipulierte oder synthetische audiovisuelle Medien,
meist erzeugt mit Hilfe von KI – finden in verschiedensten Kontexten Anwendung: von Politik über Pornografie und Kriminalität bis hin zu Wirtschaft, Strafverfolgung, Kunst, Satire, Bildung und Aktivismus. Die Studie bietet erstmals eine holistische Technikbewertung der gesellschaftlichen und ethischen Auswirkungen von Deepfakes in diesen Kontexten und untersucht mögliche Reaktionen auf die neue Technologie – von (supra-)nationaler Regulierung bis hin zu KI-basierter Deepfake-Detektion. Sie richtet zudem konkrete Handlungsempfehlungen etwa an Politik, Forschungsförderung und BürgerInnen. Die enthaltene interaktive Lehreinheit fördert die Medienkompetenz zu Deepfakes.Digitalzeitalter - Digitalgesellschaft. Das Ende des Industriezeitalters und der Beginn einer neuen Epochehttps://puma.ub.uni-stuttgart.de/bibtex/2800a2c8d35ae8d52b65961362b505804/droesslerdroessler2022-01-27T22:30:29+01:00Communication Economic Mass Sciences Social Sociology digital digitalisierung epistemologie in inequality mass media revolution sciences sociology structure <span data-person-type="editor" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="editor"><a title="Oliver Stengel" itemprop="url" href="/person/17bf6f99511f580be373d7227adc3db00/editor/0"><span itemprop="name">O. Stengel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="editor"><a title="Alexander van Looy" itemprop="url" href="/person/17bf6f99511f580be373d7227adc3db00/editor/1"><span itemprop="name">A. van Looy</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="editor"><a title="Stephan Wallaschkowski" itemprop="url" href="/person/17bf6f99511f580be373d7227adc3db00/editor/2"><span itemprop="name">S. Wallaschkowski</span></a></span></span> (Eds.) </span><span class="additional-entrytype-information"><em>SpringerLink </em><em><span itemprop="publisher">Springer VS</span>, </em><em>Wiesbaden, </em>(<em><span>2017<meta content="2017" itemprop="datePublished"/></span></em>)</span>Thu Jan 27 22:30:29 CET 2022WiesbadenSpringerLinkDigitalzeitalter - Digitalgesellschaft. Das Ende des Industriezeitalters und der Beginn einer neuen Epoche2017Communication Economic Mass Sciences Social Sociology digital digitalisierung epistemologie in inequality mass media revolution sciences sociology structure Debatten im Netz: Dunning-Kruger-Effekt: Zu dummhttps://puma.ub.uni-stuttgart.de/bibtex/234a168b9d8860ab1627b76bd140767aa/droesslerdroessler2021-10-13T01:20:30+02:00dunning-kruger-effekt internet kommunikation media medien psychologie social sozialpsychologie <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kathrin Passig" itemprop="url" href="/person/1cf74aa65ed6dd17ebd158fd8e5603382/author/0"><span itemprop="name">K. Passig</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Frankfurter Rundschau</span>, </em> </span>(<em><span>Oct 12, 2021<meta content="Oct 12, 2021" itemprop="datePublished"/></span></em>)</span>Wed Oct 13 01:20:30 CEST 2021Frankfurter Rundschau10Debatten im Netz: Dunning-Kruger-Effekt: Zu dumm2021dunning-kruger-effekt internet kommunikation media medien psychologie social sozialpsychologie 12What increases (social) media attention: Research impact, author
prominence or title attractiveness?https://puma.ub.uni-stuttgart.de/bibtex/22042deb8c453848ca1c52de68e6f8129/droesslerdroessler2020-01-27T23:03:57+01:00media metrics metriken publications scientific social <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Olga Zagovora" itemprop="url" href="/person/193df3ab50cf433fb39081c50b60ff6e5/author/0"><span itemprop="name">O. Zagovora</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Katrin Weller" itemprop="url" href="/person/193df3ab50cf433fb39081c50b60ff6e5/author/1"><span itemprop="name">K. Weller</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Milan Janosov" itemprop="url" href="/person/193df3ab50cf433fb39081c50b60ff6e5/author/2"><span itemprop="name">M. Janosov</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Claudia Wagner" itemprop="url" href="/person/193df3ab50cf433fb39081c50b60ff6e5/author/3"><span itemprop="name">C. Wagner</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Isabella Peters" itemprop="url" href="/person/193df3ab50cf433fb39081c50b60ff6e5/author/4"><span itemprop="name">I. Peters</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2018<meta content="2018" itemprop="datePublished"/></span></em>)<em>cite arxiv:1809.06299Comment: Paper presented at 23rd International Conference on Science and Technology Indicators (STI 2018) in Leiden, The Netherlands.</em></span>Mon Jan 27 23:03:57 CET 2020cite arxiv:1809.06299Comment: Paper presented at 23rd International Conference on Science and Technology Indicators (STI 2018) in Leiden, The NetherlandsWhat increases (social) media attention: Research impact, author
prominence or title attractiveness?2018media metrics metriken publications scientific social Do only major scientific breakthroughs hit the news and social media, or does
a 'catchy' title help to attract public attention? How strong is the connection
between the importance of a scientific paper and the (social) media attention
it receives? In this study we investigate these questions by analysing the
relationship between the observed attention and certain characteristics of
scientific papers from two major multidisciplinary journals: Nature
Communication (NC) and Proceedings of the National Academy of Sciences (PNAS).
We describe papers by features based on the linguistic properties of their
titles and centrality measures of their authors in their co-authorship network.
We identify linguistic features and collaboration patterns that might be
indicators for future attention, and are characteristic to different journals,
research disciplines, and media sources.What increases (social) media attention: Research impact, author prominence or title attractiveness?Online Social Network Revolutionhttps://puma.ub.uni-stuttgart.de/bibtex/29f53255a3b2f13e1af52655cf029319b/malte.heckelenmalte.heckelen2017-10-25T14:04:56+02:00analysis, diffusion graph information media media, network social twitter, <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hariton Efstathiades" itemprop="url" href="/person/1b86f4c3c404ac849eb1ac1d25d9501e5/author/0"><span itemprop="name">H. Efstathiades</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Demetris Antoniades" itemprop="url" href="/person/1b86f4c3c404ac849eb1ac1d25d9501e5/author/1"><span itemprop="name">D. Antoniades</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="George Pallis" itemprop="url" href="/person/1b86f4c3c404ac849eb1ac1d25d9501e5/author/2"><span itemprop="name">G. Pallis</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Marios D Dikaiakos" itemprop="url" href="/person/1b86f4c3c404ac849eb1ac1d25d9501e5/author/3"><span itemprop="name">M. Dikaiakos</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Zoltán Szlávik" itemprop="url" href="/person/1b86f4c3c404ac849eb1ac1d25d9501e5/author/4"><span itemprop="name">Z. Szlávik</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert-Jan Sips" itemprop="url" href="/person/1b86f4c3c404ac849eb1ac1d25d9501e5/author/5"><span itemprop="name">R. Sips</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">2016 IEEE International Conference onBig Data)</span>, </em></span><em>page <span itemprop="pagination">626--635</span>. </em><em>IEEE, </em>(<em><span>2016<meta content="2016" itemprop="datePublished"/></span></em>)</span>Wed Oct 25 14:04:56 CEST 20172016 IEEE International Conference onBig Data)626--635Online Social Network Revolution2016analysis, diffusion graph information media media, network social twitter, In 2010 the popular paper by Kwak et al. [11] presented the first comprehensive study of Twitter as it appeared in 2009, using most of the Twitter network at the time. Since then, Twitter's popularity and usage has exploded, experiencing a 10-fold increase. As of 2015, it has more than 500 million users, out of which 316 million are active, i.e. logging into the service at least once a month.1 In this study we revisit the network observed by Kwak et al. to examine the changes exhibited in both the graph and the behavior of the users in it. Our results conclude to a denser network, showing an increase in the number of reciprocal edges, despite the fact that around 12.5% of the 2009 users have now left Twitter. However, the network's largest strongly connected component seems to be significantly decreasing, suggesting a movement of edges towards popular users. Furthermore, we observe numerous changes in the lists of influential Twitter users, having several accounts that where not popular in the past securing a position in the top-20 list as new entries.Peers and Sources As Social Capital in the Production of Newshttps://puma.ub.uni-stuttgart.de/bibtex/2368c554a79cb94e04b718dbacb9303f4/malte.heckelenmalte.heckelen2017-10-25T14:04:56+02:00analysis analysis, communities, gatekeeping, journalism, media media, network online social <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maurice Vergeer" itemprop="url" href="/person/1205d9c9e95f399d4e2fe7516ced8b291/author/0"><span itemprop="name">M. Vergeer</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Soc. Sci. Comput. Rev.</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">33 </span></span>(<span itemprop="issueNumber">3</span>):
<span itemprop="pagination">277--297</span></em> </span>(<em><span>June 2015<meta content="June 2015" itemprop="datePublished"/></span></em>)</span>Wed Oct 25 14:04:56 CEST 2017Thousand Oaks, CA, USASoc. Sci. Comput. Rev.jun3277--297Peers and Sources As Social Capital in the Production of News332015analysis analysis, communities, gatekeeping, journalism, media media, network online social In a very short time span, Twitter has become a major force in modern societies and also in the production of news by journalists. How journalists use Twitter is studied extensively, particularly on a small scale i.e., qualitative research, specific events, mostly descriptive. However, studies on how Twitter has impacted journalism as a whole are relatively scarce. This study focuses on the adoption of Twitter and its emerging community network structure in the Netherlands. Using the social network data of 2,152 journalists as retrieved from Twitter, analysis shows that the social network among journalists is well connected. The journalists who are extremely popular are also able to influence the flow of information through the network more than others cf. gatekeeper role. Still, even though gatekeeping positions in the network are present due to the absence of specific relations, and the network consists of eight tightly knit network communities, the entire network is very well connected. The adoption of Twitter as a microblogging and networking service over time indicated that adoption increased particularly in early 2009. The possible consequences of these tightly knit communities for the production of news are discussed in terms of pack journalism, echo chambers, and information cascades.Der (des)informierte Bürger im Netz. Wie soziale Medien die Meinungsbildung verändernhttps://puma.ub.uni-stuttgart.de/bibtex/2a35d66c912f7eab74c5a61f771a60b10/droesslerdroessler2017-07-31T23:59:57+02:00demokratie echokammer fake filterblase journalismus kommunikation lügen media meinungsfreiheit news polarisierung politik social <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Wolfgang Schweiger" itemprop="url" href="/person/176213388fb5562b18758da6b7edcbd85/author/0"><span itemprop="name">W. Schweiger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2017<meta content="2017" itemprop="datePublished"/></span></em>)</span>Mon Jul 31 23:59:57 CEST 2017Der (des)informierte Bürger im Netz. Wie soziale Medien die Meinungsbildung verändern2017demokratie echokammer fake filterblase journalismus kommunikation lügen media meinungsfreiheit news polarisierung politik social Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approachhttps://puma.ub.uni-stuttgart.de/bibtex/246d57ac77c3dfce4b682c0d0e9b1ed77/dr.romanklingerdr.romanklinger2017-03-31T18:24:06+02:00extremism hate media mining myown nlp right-wing social speech <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Matthias Hartung" itemprop="url" href="/person/15f3f12be6eb4013165833920005398ee/author/0"><span itemprop="name">M. Hartung</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Roman Klinger" itemprop="url" href="/person/15f3f12be6eb4013165833920005398ee/author/1"><span itemprop="name">R. Klinger</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Franziska Schmidtke" itemprop="url" href="/person/15f3f12be6eb4013165833920005398ee/author/2"><span itemprop="name">F. Schmidtke</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lars Vogel" itemprop="url" href="/person/15f3f12be6eb4013165833920005398ee/author/3"><span itemprop="name">L. Vogel</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings</span>, </em></span><em>page <span itemprop="pagination">320--325</span>. </em><em>Cham, </em><em><span itemprop="publisher">Springer International Publishing</span>, </em>(<em><span>2017<meta content="2017" itemprop="datePublished"/></span></em>)</span>Fri Mar 31 18:24:06 CEST 2017ChamNatural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings320--325Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach2017extremism hate media mining myown nlp right-wing social speech An Empirical, Quantitative Analysis of the Differences Between Sarcasm and Ironyhttps://puma.ub.uni-stuttgart.de/bibtex/2a565f08265f08e955343158dd7a88b9b/dr.romanklingerdr.romanklinger2017-03-31T18:24:06+02:00classification imported irony media myown nlp sarcasm social <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jennifer Ling" itemprop="url" href="/person/1f576a431b1c9eb41c03125538e04d18b/author/0"><span itemprop="name">J. Ling</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Roman Klinger" itemprop="url" href="/person/1f576a431b1c9eb41c03125538e04d18b/author/1"><span itemprop="name">R. Klinger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">The Semantic Web: ESWC 2016 Satellite Events, Heraklion, Crete, Greece, May 29 -- June 2, 2016, Revised Selected Papers</span>, </em></span><em>page <span itemprop="pagination">203--216</span>. </em><em><span itemprop="publisher">Springer International Publishing</span>, </em>(<em><span>2016<meta content="2016" itemprop="datePublished"/></span></em>)</span>Fri Mar 31 18:24:06 CEST 2017The Semantic Web: ESWC 2016 Satellite Events, Heraklion, Crete, Greece, May 29 -- June 2, 2016, Revised Selected Papers203--216Lecture Notes in Computer ScienceAn Empirical, Quantitative Analysis of the Differences Between Sarcasm and Irony2016classification imported irony media myown nlp sarcasm social Schrott im Netz. Wie Social Bots das Internet gefährdenhttps://puma.ub.uni-stuttgart.de/bibtex/2cca5768297133b20968231ce07e0f735/droesslerdroessler2016-08-20T23:27:11+02:00bots data facebook media meinungsbildung mining political politik social twitter <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Eva Mühle" itemprop="url" href="/person/12ab7825052e40b418a507898ec0f72bd/author/0"><span itemprop="name">E. Mühle</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Handelsblatt</span>, </em> </span>(<em><span>Jul 19, 2016<meta content="Jul 19, 2016" itemprop="datePublished"/></span></em>)</span>Sat Aug 20 23:27:11 CEST 2016Handelsblatt07Schrott im Netz. Wie Social Bots das Internet gefährden2016bots data facebook media meinungsbildung mining political politik social twitter 19