Opening the black box of perceived quality: Predicting endorsement on a blog site
| Autor: | Sotirakou, C., Trilling, D., Germanakos, P., Mourlas, C., Barnaghi, P., Gottlob, G., Manolopoulos, Y., Tzouramanis, T., Vakali, A. |
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| Přispěvatelé: | Political Communication & Journalism (ASCoR, FMG) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science media_common.quotation_subject 02 engineering and technology Document management system Public relations computer.software_genre Computing Methodologies Text processing 020204 information systems 0202 electrical engineering electronic engineering information engineering Computational journalism 020201 artificial intelligence & image processing Journalism Quality (business) business computer News media Reputation media_common |
| Zdroj: | WI Proceedings: 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2019): Thessaloniki, Greece,13–17 October 2019, 388-392 STARTPAGE=388;ENDPAGE=392;TITLE=Proceedings: 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2019) |
| Popis: | Uncovering their readers’ perceptions is of key importance for every news media organization to find methods to improve the quality of their product. It has the potential to facilitate journalists’ work in attracting attention and gaining a loyal audience. Discovering which elements of a news story influence readers’ perceptions has been a cross-disciplinary research goal for the past years, because it can play a crucial role in news dissemination and consumption in the digital age. Drawing upon literature in the various areas such as journalism, psychology, computer science, and AI, this paper proposes a machine learning approach that explores three dimensions of article features that can help predicting the online behavior of the reader. Results show that how the story is written, the topic, and certain aspects of the author’s online reputation can affect reader endorsements and the perceived quality of an article. CCS CONCEPTS • Computing methodologies → Natural language processing; • Applied computing → Document management and text processing. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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