Tracking Digitally Consumed News

Poster presented at Etmaal van de Communicatiewetenschap 2015, 3 February 2015, Antwerp, Belgium.

 

The digitization of journalism has increasingly enabled news organizations to monitor the behavior of online news users by using metric tools such as Google Analytics or Chartbeat.[1] Large screens in newsrooms show real-time numbers of the amount of visitors on a news website, allowing editors to adjust the contents of their websites adherently (Anderson, 2011; MacGregor, 2007; Vu, 2014). Gathering this type of data is grounded in the tradition of audience measurement devices which started in the US in the 1950s and consolidated in the 1970 when the first people meters were installed to monitor how long, when, and what programs have been watched on television (Vicente-Marino, 2013, p. 43). With the advent of online media, it has become possible to also track online news consumption starting around the year 2000 (Coffey, 2001). While metric tools gather information of individual websites, tracking of online user consumption of a group of respondent is a booming business. Even though ethical questions when monitoring users’ online behaviour remain (Lotz, 2004) and scholars question the meaning of a click – does it e.g. mean someone is interested in the news? And does a non-click also mean non-interest? (Costera Meijer & Groot Kormelink, 2014, p. 10) -, several research companies developed trackers that monitor respondents online behaviour both on desktop, laptop, mobile and tablet. In the US, Nielsen created the Online Netview Panel and the Dutch companies TNS Nipo and Wakoopa offers similar tools.[2] In the Netherlands the Dutch Digital Media Measurement (DDMM) research distributes periodical overviews of the most visited websites in the Netherlands on all platforms and devices.[3]

However, most of this type of research creates lists of aggregated visits to websites, considering website visitors as commodity (Richardson, 2007, p. 79; Usher, 2013) in order to give advertisers detailed information on how to reach their target audience in the most efficient manner. Feedback to journalists is limited to presenting the most clicked items often leading to the critique that most news users are more interested in trivial news than in public affairs (Boczkowski, Mitchelstein, & Walter, 2011; Karlsson & Clerwall, 2013; Nederlandse Nieuwsmonitor, 2013). Given the focus on the most read articles, relatively little is known about all consumed news articles, the contents of the visited news articles, let alone the patterns of news consumption over the day. Do news users e.g. read in the morning mainly about sports, during lunch about gossip and in the evening about politics? And what is their checking round’? Do they often visit certain websites in the same order? (Costera Meijer & Groot Kormelink, 2014)

Up until now, these types of research questions are mainly addressed by using diary methods relying on the memory of the participants (Vicente-Marino, 2013, p. 49), while tracking tools could give an objective indication of the actual visits to websites. Therefore, this poster presents the set-up of a research design that monitors the actual consumption of news websites on desktop and laptop computers by the use of a proxy installed on the devices of a group of respondents.[4] This set-up is in line with Findahl (2013) who investigated the online behaviour of an American family and Menchen-Trevino (2012) that used a special-designed proxy to monitor the exposure to political communication during the November 2010 U.S. general election campaign.

However, like the corporate studies such as DDMM and Nielsen, these academic studies only report the website titles that have been visited. Our set-up goes two steps further. We do not only monitor the website titles but also the actual visited URLs and we crawl all textual and visual contents of the visited websites. Since one of the problems when monitoring a person’s online behaviour is the magnitude of the data that is being collected (Batista & Silva, 2002; Manovich, 2012; Vicente-Marino, 2013, p. 43), we deploy automated content analyses techniques (Atteveldt, 2008; Bhulai, Kampstra, Kooiman, Koole, & Kok, 2012; Kleinneijenhuis & Atteveldt, 2006) to detect the topics that are being discussed in the news items. This enables us to calculate the topical online news consumption during the day.

Literature

Anderson, C. W. (2011). Between creative and quantified audiences: Web metrics and changing patterns of newswork in local US newsrooms. Journalism, 12(5), 550–566. doi:10.1177/1464884911402451

Atteveldt, W. van. (2008). Semantic Network Analysis: Techniques for Extracting, Representing, and Querying Media Content. BookSurge.

Batista, P., & Silva, M. (2002). Mining Web Access Logs of an On-line Newspape. Presented at the Proceedings of theWorkshop on Recommendation and Personalization in eCommerce of the 2nd International Conferenceon Adaptive Hypermedia and Adaptive Web Based Systems, Malaga. Retrieved from http://xldb.di.fc.ul.pt/xldb/publications/rpec02.pdf

Bhulai, S., Kampstra, P., Kooiman, L., Koole, G., & Kok, B. (2012). Trend visualization on Twitter: What’s hot and what’s not? (pp. 43–48). Presented at the IARIA, Barcelona.

Boczkowski, P. J., Mitchelstein, E., & Walter, M. (2011). Convergence Across Divergence: Understanding the Gap in the Online News Choices of Journalists and Consumers in Western Europe and Latin America. Communication Research, 38(3), 376–396. doi:10.1177/0093650210384989

Coffey, S. (2001). Internet Audience Measurement: A Practicioner’s View. Journal of Interactive Advertising, 1(2), 10–17.

Costera Meijer, I., & Groot Kormelink, T. (2014). Checking, Sharing, Clicking and Linking. Digital Journalism, 0(0), 1–16. doi:10.1080/21670811.2014.937149

Findahl, O., Lagerstedt, C., & Aurelius, A. (2013). Triangulation as a way to validate and deepen the knowledge about user behavior. A comparison between questionnaires, diaries and traffic measurement. In G. Patriarche, H. Bilandzic, J. L. Jensen, & J. Juriši?, Audience Research Methodologies: Between innovation and consolidation (pp. 54–69). New York.

Karlsson, M., & Clerwall, C. (2013). Negotiating Professional News Judgment and “Clicks.” Nordicom Review, 34(2), 65–76. doi:10.2478/nor-2013-0054

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Manovich, L. (2012). How to Follow Software Users? Retrieved from http://lab.softwarestudies.com/2012/04/new-article-lev-manovich-how-to-follow.html

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Vu, H. T. (2014). The online audience as gatekeeper: The influence of reader metrics on news editorial selection. Journalism, 15(8), 1094–1110. doi:10.1177/1464884913504259

[1] http://www.google.com/analytics/ , https://chartbeat.com/

[2] http://en-us.nielsen.com/sitelets/cls/digital/online-netview.html, http://www.tns-nipo.com/ons-aanbod/marktonderzoek/digital/digital-analytics/ , http://wakoopa.com/

[3] http://www.vinex.nl/ddmm/

[4] This research is part of the larger project the New News Consumer in which major Dutch news outlets participate, see www.news-use.com Our partners will provide the respondents for the fieldwork guaranteeing a mixed and wide range of participants.