Most of our knowledge about online news consumption comes from survey-based news market reports, partial usage data from a single editor, or what people publicly share on social networks. This paper complements these sources by presenting the first holistic study of visits across online news outlets that a population uses to read news. We monitor the entire network traffic generated by Internet users in four locations in Italy. Together these users generated 80 million visits to 5.4 million news articles in about one year and a half. This unique view allows us to evaluate how usage data complements existing data sources. We find for instance that only 16% of news visits in our datasets came from online social networks. In addi- tion, the popularity of news categories when considering all visits is quite different from the one when considering only news discovered on social media, or visits to a single major news outlet. Interestingly, a substantial mismatch emerges be- tween self-reported news-category preferences (as measured by Reuters Institute in the same year and same country) and their actual popularity in terms of visits in our datasets. In particular, unlike self-reported preferences expressed by users in surveys that put “Politics”, “Science” and “International” as the most appreciated categories, “Tragedies and Weird news"’ and “Sport” are by far the most visited. We discuss two pos- sible causes of this mismatch and conjecture that the most plausible reason is the disassociation that may occur between individuals’ cognitive values and their cue-triggered attraction.

The News We Like Are Not the News We Visit: News Categories Popularity in Usage Data / Ben Houidi, Zied; Scavo, Giuseppe; Traverso, Stefano; Teixeira, Renata; Mellia, Marco; Ganguly, Soumen. - ELETTRONICO. - (2019), pp. 1-12. ((Intervento presentato al convegno 13TH INTERNATIONAL AAAI CONFERENCE ON WEB AND SOCIAL MEDIA (ICWSM-2019) tenutosi a Munich, DE nel 11- 14 June 2019.

The News We Like Are Not the News We Visit: News Categories Popularity in Usage Data

Marco Mellia;
2019

Abstract

Most of our knowledge about online news consumption comes from survey-based news market reports, partial usage data from a single editor, or what people publicly share on social networks. This paper complements these sources by presenting the first holistic study of visits across online news outlets that a population uses to read news. We monitor the entire network traffic generated by Internet users in four locations in Italy. Together these users generated 80 million visits to 5.4 million news articles in about one year and a half. This unique view allows us to evaluate how usage data complements existing data sources. We find for instance that only 16% of news visits in our datasets came from online social networks. In addi- tion, the popularity of news categories when considering all visits is quite different from the one when considering only news discovered on social media, or visits to a single major news outlet. Interestingly, a substantial mismatch emerges be- tween self-reported news-category preferences (as measured by Reuters Institute in the same year and same country) and their actual popularity in terms of visits in our datasets. In particular, unlike self-reported preferences expressed by users in surveys that put “Politics”, “Science” and “International” as the most appreciated categories, “Tragedies and Weird news"’ and “Sport” are by far the most visited. We discuss two pos- sible causes of this mismatch and conjecture that the most plausible reason is the disassociation that may occur between individuals’ cognitive values and their cue-triggered attraction.
File in questo prodotto:
File Dimensione Formato  
icwsm19_camera_ready.pdf

non disponibili

Descrizione: camera ready
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 257.38 kB
Formato Adobe PDF
257.38 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
3212-Article Text-6261-1-10-20190531.pdf

non disponibili

Descrizione: versione finale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 2.85 MB
Formato Adobe PDF
2.85 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2751332
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo