TY  - GEN
N2  - This empirical thesis analyses the impact of sentiments in online media on consumers, businesses, and society as a whole, and how knowledge of these correlations can be used in a variety of applications. The results show that the sentiment data can be employed in a variety of ways, functioning as an interesting new explanatory variable to complement and approximate survey data in areas such as tourism demand, consumer confidence, and many more. In particular, the cross-country sentiment analysis reveals compelling information on media biases, the reporting on alternative truths, and countries as a filter bubble. In addition to quantitative comparisons, the descriptive statistics reveal important information on the sentiment developments across countries. While this research is able to provide interesting findings for real-world applications for consumers, businesses, and society, the awareness of a media landscape that is heavily and increasingly dominated by negative news is particularly striking. Thus, in addition to the actual applications, above all, the thesis shows the media landscape in which everyone must act in the future. About the author Kejo Starosta is an independent researcher interested in computational text analysis and the large-scale retrieval of unstructured text data from the web. Besides being passionate about computer science, he uses his qualitative text data for econometric modeling to nowcast, forecast, and model various aspects of the economy.
DO  - 10.1007/978-3-658-36729-9
DO  - doi
AB  - This empirical thesis analyses the impact of sentiments in online media on consumers, businesses, and society as a whole, and how knowledge of these correlations can be used in a variety of applications. The results show that the sentiment data can be employed in a variety of ways, functioning as an interesting new explanatory variable to complement and approximate survey data in areas such as tourism demand, consumer confidence, and many more. In particular, the cross-country sentiment analysis reveals compelling information on media biases, the reporting on alternative truths, and countries as a filter bubble. In addition to quantitative comparisons, the descriptive statistics reveal important information on the sentiment developments across countries. While this research is able to provide interesting findings for real-world applications for consumers, businesses, and society, the awareness of a media landscape that is heavily and increasingly dominated by negative news is particularly striking. Thus, in addition to the actual applications, above all, the thesis shows the media landscape in which everyone must act in the future. About the author Kejo Starosta is an independent researcher interested in computational text analysis and the large-scale retrieval of unstructured text data from the web. Besides being passionate about computer science, he uses his qualitative text data for econometric modeling to nowcast, forecast, and model various aspects of the economy.
T1  - Measuring the impact of online media on consumers, businesses and society /
AU  - Starosta, Kejo,
CN  - P94
ID  - 1444958
KW  - Mass media
KW  - Social media
KW  - Digital media.
KW  - Médias
KW  - Médias numériques.
SN  - 9783658367299
SN  - 3658367296
TI  - Measuring the impact of online media on consumers, businesses and society /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-658-36729-9
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-658-36729-9
ER  -