Algorithmic news consumption

I regularly consume news in a number of different ways. Some of this consumption is entirely intentional, some incidental, and a lot of my news consumption has been algorithmically curated to reduce effort expended on my part. I enjoy engaging with news through short-form content, with the option to click into articles of interest from deliberately varied sources, chosen with consideration in an attempt to prevent bias caused by source location, political leaning or demographic pandering.

“Algorithmic news consumption” is the consumption of news content that has been generated or distributed automatically through algorithms. The habitual use of algorithms can have an influence on the interpretation and classification of ‘news-worthy’ topics. News consumers should consider how and where they source their news, and the impact that a chosen news source may have on their understanding and interpretation of the world.

I consider the ‘liking’ and ‘following’ of choice accounts as an intentional and conscious attempt to curate my newsfeeds, providing me with the type of news and content that I wish to see. Lu (2020) defines the act of news curation as a process of evaluating and selecting information with the aim of utilising an algorithm to present useful, relevant, or meaningful content for the news consumer. Park and Kaye (2019) define news consumption as the ‘reconstructuring, reformulating, repurposing, reframing and sharing of news through social media’. In this way, ‘liking’ or ‘following’ selected accounts is considered as an intentional and conscious attempt to curate a user’s preferred newsfeed. I feel that curating my newsfeed helps me to exert a type of control and sense of order in relation to the type of content that I am presented with and consuming online.

In addition to my social-media news consumption, my husband and I have a physical newspaper subscription to The Saturday Paper which we read together on the weekend. We have also developed a routine where we discuss the email wrap of daily news headlines that we receive from ‘Post’ as we eat our breakfast each morning. I am also regularly exposed to Hobart’s local newspaper, ‘The Mercury’ in the course of my work, as I monitor it for relevant topical stories or information.

While these news consumption habits are tied to the same news source-type (a newspaper), my consumption of the contents of each news provider are entirely different. Even when reading a traditional physical newspaper, I may choose to read a different set of articles from my husband. Therefore, it could be argued that news content is always curated and personalised where selection or filtering of content consumption can occur.

However, these curation practices arguably become more important in an online environment where algorithms govern the circulation of news.

Researchers have found that many individuals using content curation methods are accurately categorized as interested in news or politics and are successful in attracting their preferred content to their newsfeed (Thorston et al. 2019; Merten 2020; Park & Kaye 2019). However, by reducing the intentionality of their news consumption users may increase the likelihood of disengaging with long-form journalism, instead placing trust in algorithms to provide simplified content with sufficient explanation so that they may maintain general oversight of current events.

Furthermore, the visibility of news and politics in a user’s newsfeed depends on the user’s actions, the actions of their ‘friends’, content publishers, and the algorithm built into the social media platform of their choosing. The algorithm infers their level of interest by tracking their behaviour and the overall level of interest displayed by them over time (Thorson et.al, 2019).

While news consumers may willingly reduce their personal responsibility for news consumption when relying on algorithms, Lee et.al (2019) argues that a certain level of control can be maintained through the utilisation of built-in features. The algorithm can be influenced by ‘liking’ or ‘following’ posts from accounts of interest, or by ‘hiding’ and ‘reporting’ posts or content that the user does not wish to engage with.

Thorston et.al (2019) argues that the algorithm’s categorisation of users can also affect their level of exposure to news and political messaging, often to an extent beyond their self-reported level of interest. A study undertaken by Lee et.al (2019) found that individuals were more likely to engage in news curation that encouraged algorithims to prioritise content that they liked than they were to unfollow or block content that they did not. This was commonly attributed to a fear of missing ‘important information or news’ that may be shared by the publisher in future (Lee et.al, 2019).

News curation methodologies introduced in years prior may not be as effective in current times. When Facebook first rose to prominence in the early 2010s it actively sought to position itself as a news media platform (Meese and Hurcombe 2020) to increase revenue through associated online advertising. However, the business strategy changed in 2018, prioritising posts from users’ family and friends to retain traffic on the Facebook site and disincentivise clicking through to articles hosted on external websites (Meese and Hucombe 2020; Bailo et al. 2021).

The platforms that are used to consume news may also affect the way that news is understood. Social media does not curate its content in the same way that a news publisher or broadcaster does (Lu 2020). While traditional media is developed under the supervision of an editor, with a clear beginning, middle, and end (Lu 2020), algorithms are designed to deliver information that will encourage the user to continue to engage with the platform.

Considering our news consumption habits can be illuminating. There are risks to relying on algorithms to curate consumption habits, and a ‘set and forget’ approach may decrease the likelihood of conscious engagement with long-form news. To be intentional and considerate about news consumption requires increased attention to the context, simplification, prominence, and real or imagined relationships surrounding the piece of news, which may skew an individual’s perception of a story.  Users should consider their habits around news consumption and counter any impact on their understanding of and interaction with the wider world because of algorithmic bias.