Abstract
This work in progress reports on ongoing experimentation with machine learning approaches on time series data, where the time series is a quantification of the success of content about a certain topic published on a certain digital channel over a past time period. The experiment tests how accurate predictive analytical approaches can be to predict the future success of a piece of media content published on the Web or social media platform according to its topics. Our intention is to enable a new innovation in media organizations’ content publication strategies, where the choice of media for a future publication can be informed by such predictive capabilities in order to maximize the potential content's reach to a digital audience.
Original language | English |
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Title of host publication | Work in Progress track at ACM IMX 2020 (online) |
Pages | 185-188 |
DOIs | |
Publication status | Published - 17 Jun 2020 |
Event | ACM International Conference on Interactive Media Experiences 2020: ACM IMX 2020 - Duration: 17 Jun 2020 → 19 Jun 2020 |
Conference
Conference | ACM International Conference on Interactive Media Experiences 2020 |
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Period | 17/06/2020 → 19/06/2020 |