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Papers by Fenja De Silva-Schmidt
Qualität im Gesundheitsjournalismus, 2014
Conference Paper for the Future of Journalism conference 2015: Risks, Threats and Opportunities, ... more Conference Paper for the Future of Journalism conference 2015: Risks, Threats and Opportunities, September 10-11th 2015, Cardiff University, UK.
Abstract:
For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly relevant: First, it is a topic worth covering so that the related developments and their consequences are made understandable and debatable for the public. Second, the ‘computational turn’ has already begun to affect practices of news production and is giving rise to novel ways to identify and tell stories. Thus, what we observe is the emergence of a new journalistic sub-field mostly described as ‘computational/data journalism’. This study focuses on the output of data journalism – with the aim of contributing to a better understanding of its reporting styles. The method used is a classical ‘handmade’ standardised content analysis. The sample consists of all the pieces that were nominated for the Data Journalism Award (DJA) – an award issued annually by the Global Editors Network – in 2013 and 2014 (n= 120). Categories of analysis look at, amongst other aspects, data sources and types, visualisation strategies, interactive features, topics, and types of nominated media outlets. Results show that over 40 percent of the data-driven pieces were published on the websites of (daily or weekly) newspapers; just over 20 Percent came mainly from non-profit organisations for investigative journalism like ProPublica. Almost half of the cases cover a political topic, and social and scientific issues appear frequently too. Financial data and geodata are the types of data used most often and most of the data relates to a national context. More than two-thirds of the projects use data from official sources like Eurostat. Further analyses regard differences between 2013 and 2014 and look deeper into visualisation strategies and interactive features.
Drafts by Fenja De Silva-Schmidt
For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly rel... more For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly relevant: First, it is a topic worth covering so that the related developments and their consequences are made understandable and debatable for the public. Second, the ‘computational turn’ has already begun to affect practices of news production and is giving rise to novel ways of identifying and telling stories. What we observe as a result is the emergence of a new journalistic sub-field often described as ‘computational/data journalism’. This study focuses on the output of data journalism; by using a classic 'handmade' standardised content analysis methodology it aims to contribute to a better understanding of its reporting styles. The sample consists of all the pieces that were nominated for the Data Journalism Award (DJA) – an award issued annually by the Global Editors Network – from 2013 to 2015 (n= 179). Our categories of analysis look at, amongst other aspects, data sources and types, visualisation strategies, interactive features, topics, and types of media outlets nominated. Results show that over 40 percent of the data-driven pieces were published on the websites of (daily or weekly) newspapers and nearly 20 percent came from non-profit organisations for investigative journalism like ProPublica. Almost half of the cases cover a political topic, and social, economic as well as health and science issues appear frequently too. Financial data and geodata are the types of data used most often and most of the data relates to a national context. More than two-thirds of the projects use data from an official source like Eurostat. Further analyses regard the differences between 2013, 2014 and 2015 and look deeper into visualisation strategies and interactive features.
Research reports by Fenja De Silva-Schmidt
Die Entstehung des Datenjournalismus kann als Antwort des Journalismus auf die „Datafizierung“ de... more Die Entstehung des Datenjournalismus kann als Antwort des Journalismus auf die „Datafizierung“ der Gesellschaft verstanden werden: In der Auseinandersetzung mit dem Phänomen „Big Data“ entwickelt der Journalismus neue Wege, Geschichten (in Daten) zu identifizieren und (mit Daten) zu erzählen. Von Journalismusforschern wie -praktikern wird das dabei entstehende Berichterstattungsmuster häufig als die Zukunft des Journalismus angesehen, vor allem aber als genuin für den Onlinejournalismus. Aus Sicht der Forschung ist jedoch noch nicht einmal der Status Quo des ohnehin sehr dynamischen Datenjournalismus geklärt: Noch wissen wir wenig insbesondere über das, was den Datenjournalismus als Berichterstattungsmuster ausmacht, nämlich die datenjournalistischen Beiträge sowie die spezifischen inhaltlichen und darstellerischen Elemente, aus denen sie bestehen und die sie von anderen Formen der Berichterstattung abgrenzen. Der Schwerpunkt dieser Studie liegt daher auf den Produkten des Datenjournalismus: Mithilfe einer standardisierten Inhaltsanalyse untersuchen wir datenjournalistische Projekte, die man als „Goldstandard“ datengetriebener Berichterstattung betrachten kann – Projekte, die von 2013 bis 2015 (N = 179) fur einen der Data Journalism Awards (DJA) nominiert wurden, einen jährlich vom Global Editors Network in unterschiedlichen Kategorien vergebenen Preis. Untersucht wurden unter anderem die genutzten Datenarten und -quellen, Visualisierungsstrategien, Interaktionsmöglichkeiten, die behandelten Themen sowie die Medienangebote, von denen die Beiträge stammen.
Die Ergebnisse zeigen unter anderem, dass uber 40 Prozent der datengetriebenen Arbeiten auf Webseiten von Tages- oder Wochenzeitungen veröffentlicht wurden und fast 20 Prozent von Non-Profit Organisationen für investigativen Journalismus wie ProPublica stammen.
Fast die Hälfte der Fälle behandelt ein politisches Thema. Auch Gesellschafts- und Wirtschafts- sowie Gesundheits- und Wissenschaftsthemen kommen vermehrt vor. Finanz- und Geodaten sind die meistgenutzten Datenarten, wobei sich der Großteil der Datensätze auf eine nationale Ebene bezieht. In mehr als zwei Drittel der Projekte werden die Daten einer offiziellen Quelle wie zum Beispiel Eurostat verwendet. In weiteren Analysen werden die Unterschiede zwischen den Jahren 2013, 2014 und 2015 herausgearbeitet und Visualisierungsstrategien sowie Interaktionsmöglichkeiten untersucht.
Journal Articles by Fenja De Silva-Schmidt
International Journal of Communication, 2017
Professional norms of science have played an important role in discouraging scientists from raisi... more Professional norms of science have played an important role in discouraging scientists from raising their voices in public. However, they are increasingly using social media to discuss and publicize their research. This study investigates the 2015 United Nations Climate Change Conference summit and examines scientists’ social media use by analyzing “digital traces” that scientists left on social media during the summit. Using geolocated tweets, we compare the Twitter use of scientists who attended the conference with those who did not. Combining automated, quantitative, and qualitative content analysis, the study shows how scientists participating in the conference provided live reporting and formed a transnational network. Scientists at the conference and elsewhere engaged in political advocacy, indicating a shift towards a new pattern of hybrid science communication, which includes characteristics that have formerly been attributed to journalism and advocacy.
Qualität im Gesundheitsjournalismus, 2014
Conference Paper for the Future of Journalism conference 2015: Risks, Threats and Opportunities, ... more Conference Paper for the Future of Journalism conference 2015: Risks, Threats and Opportunities, September 10-11th 2015, Cardiff University, UK.
Abstract:
For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly relevant: First, it is a topic worth covering so that the related developments and their consequences are made understandable and debatable for the public. Second, the ‘computational turn’ has already begun to affect practices of news production and is giving rise to novel ways to identify and tell stories. Thus, what we observe is the emergence of a new journalistic sub-field mostly described as ‘computational/data journalism’. This study focuses on the output of data journalism – with the aim of contributing to a better understanding of its reporting styles. The method used is a classical ‘handmade’ standardised content analysis. The sample consists of all the pieces that were nominated for the Data Journalism Award (DJA) – an award issued annually by the Global Editors Network – in 2013 and 2014 (n= 120). Categories of analysis look at, amongst other aspects, data sources and types, visualisation strategies, interactive features, topics, and types of nominated media outlets. Results show that over 40 percent of the data-driven pieces were published on the websites of (daily or weekly) newspapers; just over 20 Percent came mainly from non-profit organisations for investigative journalism like ProPublica. Almost half of the cases cover a political topic, and social and scientific issues appear frequently too. Financial data and geodata are the types of data used most often and most of the data relates to a national context. More than two-thirds of the projects use data from official sources like Eurostat. Further analyses regard differences between 2013 and 2014 and look deeper into visualisation strategies and interactive features.
For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly rel... more For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly relevant: First, it is a topic worth covering so that the related developments and their consequences are made understandable and debatable for the public. Second, the ‘computational turn’ has already begun to affect practices of news production and is giving rise to novel ways of identifying and telling stories. What we observe as a result is the emergence of a new journalistic sub-field often described as ‘computational/data journalism’. This study focuses on the output of data journalism; by using a classic 'handmade' standardised content analysis methodology it aims to contribute to a better understanding of its reporting styles. The sample consists of all the pieces that were nominated for the Data Journalism Award (DJA) – an award issued annually by the Global Editors Network – from 2013 to 2015 (n= 179). Our categories of analysis look at, amongst other aspects, data sources and types, visualisation strategies, interactive features, topics, and types of media outlets nominated. Results show that over 40 percent of the data-driven pieces were published on the websites of (daily or weekly) newspapers and nearly 20 percent came from non-profit organisations for investigative journalism like ProPublica. Almost half of the cases cover a political topic, and social, economic as well as health and science issues appear frequently too. Financial data and geodata are the types of data used most often and most of the data relates to a national context. More than two-thirds of the projects use data from an official source like Eurostat. Further analyses regard the differences between 2013, 2014 and 2015 and look deeper into visualisation strategies and interactive features.
Die Entstehung des Datenjournalismus kann als Antwort des Journalismus auf die „Datafizierung“ de... more Die Entstehung des Datenjournalismus kann als Antwort des Journalismus auf die „Datafizierung“ der Gesellschaft verstanden werden: In der Auseinandersetzung mit dem Phänomen „Big Data“ entwickelt der Journalismus neue Wege, Geschichten (in Daten) zu identifizieren und (mit Daten) zu erzählen. Von Journalismusforschern wie -praktikern wird das dabei entstehende Berichterstattungsmuster häufig als die Zukunft des Journalismus angesehen, vor allem aber als genuin für den Onlinejournalismus. Aus Sicht der Forschung ist jedoch noch nicht einmal der Status Quo des ohnehin sehr dynamischen Datenjournalismus geklärt: Noch wissen wir wenig insbesondere über das, was den Datenjournalismus als Berichterstattungsmuster ausmacht, nämlich die datenjournalistischen Beiträge sowie die spezifischen inhaltlichen und darstellerischen Elemente, aus denen sie bestehen und die sie von anderen Formen der Berichterstattung abgrenzen. Der Schwerpunkt dieser Studie liegt daher auf den Produkten des Datenjournalismus: Mithilfe einer standardisierten Inhaltsanalyse untersuchen wir datenjournalistische Projekte, die man als „Goldstandard“ datengetriebener Berichterstattung betrachten kann – Projekte, die von 2013 bis 2015 (N = 179) fur einen der Data Journalism Awards (DJA) nominiert wurden, einen jährlich vom Global Editors Network in unterschiedlichen Kategorien vergebenen Preis. Untersucht wurden unter anderem die genutzten Datenarten und -quellen, Visualisierungsstrategien, Interaktionsmöglichkeiten, die behandelten Themen sowie die Medienangebote, von denen die Beiträge stammen.
Die Ergebnisse zeigen unter anderem, dass uber 40 Prozent der datengetriebenen Arbeiten auf Webseiten von Tages- oder Wochenzeitungen veröffentlicht wurden und fast 20 Prozent von Non-Profit Organisationen für investigativen Journalismus wie ProPublica stammen.
Fast die Hälfte der Fälle behandelt ein politisches Thema. Auch Gesellschafts- und Wirtschafts- sowie Gesundheits- und Wissenschaftsthemen kommen vermehrt vor. Finanz- und Geodaten sind die meistgenutzten Datenarten, wobei sich der Großteil der Datensätze auf eine nationale Ebene bezieht. In mehr als zwei Drittel der Projekte werden die Daten einer offiziellen Quelle wie zum Beispiel Eurostat verwendet. In weiteren Analysen werden die Unterschiede zwischen den Jahren 2013, 2014 und 2015 herausgearbeitet und Visualisierungsstrategien sowie Interaktionsmöglichkeiten untersucht.
International Journal of Communication, 2017
Professional norms of science have played an important role in discouraging scientists from raisi... more Professional norms of science have played an important role in discouraging scientists from raising their voices in public. However, they are increasingly using social media to discuss and publicize their research. This study investigates the 2015 United Nations Climate Change Conference summit and examines scientists’ social media use by analyzing “digital traces” that scientists left on social media during the summit. Using geolocated tweets, we compare the Twitter use of scientists who attended the conference with those who did not. Combining automated, quantitative, and qualitative content analysis, the study shows how scientists participating in the conference provided live reporting and formed a transnational network. Scientists at the conference and elsewhere engaged in political advocacy, indicating a shift towards a new pattern of hybrid science communication, which includes characteristics that have formerly been attributed to journalism and advocacy.