About this Research Topic
Currently, we are experiencing an unprecedented digital revolution. Enabled by technological progress in information technologies, the World-Wide-Web (WWW) has become an integral part of our social and professional life. For instance, we read about news and politics in online journals or newspapers, we order products from trading or auctioning platforms, we obtain information from Wikipedia, search engines, or finance platforms, and we share our views and opinions on social media. All this leads to the beginning of a global digital society which will shape our future considerably.
Despite the pervasiveness of the WWW, our knowledge of it is astonishingly limited. One reason for this lack is that a systematic analysis of any research question requires advanced data analytics methods for text, image, video, or audio data. Since the field of data science is just emerging, such advanced data analytic methods are still in their infancy. Specific problems in this context are web scraping methods for automatically extracting web data, predictive methods utilizing social media for business or health, identification of 'fake news', and integration of different data sources and visualization techniques for harnessing the complexity of big data.
The purpose of our Research Topic 'Applications of Data Analytics for Digital Society' is to bring together researchers interested in this interdisciplinary field to share information about recent progress and persistent challenges. We are particularly interested in welcoming contributions that explore any of the following research areas (but we are not limited to):
- social network analysis
- analysis of online journals and magazines
- analysis of trading and auctioning platforms and online marketplaces
- social media for marketing
- business analytics for social media
- web content mining
- text analytics
- natural language processing
- web scraping methods
- web visualization methods
Despite the pervasiveness of the WWW, our knowledge of it is astonishingly limited. One reason for this lack is that a systematic analysis of any research question requires advanced data analytics methods for text, image, video, or audio data. Since the field of data science is just emerging, such advanced data analytic methods are still in their infancy. Specific problems in this context are web scraping methods for automatically extracting web data, predictive methods utilizing social media for business or health, identification of 'fake news', and integration of different data sources and visualization techniques for harnessing the complexity of big data.
The purpose of our Research Topic 'Applications of Data Analytics for Digital Society' is to bring together researchers interested in this interdisciplinary field to share information about recent progress and persistent challenges. We are particularly interested in welcoming contributions that explore any of the following research areas (but we are not limited to):
- social network analysis
- analysis of online journals and magazines
- analysis of trading and auctioning platforms and online marketplaces
- social media for marketing
- business analytics for social media
- web content mining
- text analytics
- natural language processing
- web scraping methods
- web visualization methods
Keywords: Computational social science, Social networks, Social Media, Social media marketing, Digital journalism, Predictive analytics for politics, business, finance and health, Web scraping and mining, Text analytics, Data integration and visualization
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
