Tinius Digest February 2022
Tinius Digest
Tinius Digest report on changes, trends and developments within the media business at large. These are our key findings from last month.
Share the report with colleagues and friends, and use the content in presentations or meetings.
Insight February 2022
Kantar’s TVOV survey shows that linear TV still dominates consumption for traditional TV stations in Norway.
Four main findings:
1
Considerable age differences
On average, Norwegians consumed two hours and seven minutes of content from Norwegian TV companies daily in 2021. Among the youngest (10-19) years, consumption is 46 minutes every day.
2
VOD constitutes a small proportion
Video on demand (VOD) content from the broadcasters’ streaming services accounts for an average of 19 minutes (13%) per day.
3
Traditional TV set
Viewing on traditional TVs account for 81 percent of all viewing, while tablets, desktops and mobiles account for five percent of the total with seven minutes.
4
NRK and TV 2 – and the rest...
For the linear channels, NRK has a market share of 43 percent, followed by TV 2 (27%), Discovery (14%) and NENT (8%). NRK1 (35.9%) and TV 2’s main channel (17.8%) have a combined market share of 53.7 percent.
A survey conducted by The Norwegian Media Authority shows how widespread online hate speech is among youths and young adults.
Four main findings:
1
Greater problem for youths
25 percent of Norwegian between the age of 16 and 20 have experienced hateful comments on the internet directed at them in the past year. The proportion that has experienced hate speech among young people is more than six times higher than in the general population (4%).
2
Snapchat and TikTok
It is most common to get hateful comments on Snapchat (38%) and TikTok (26%).
3
Most are anonymous
55 percent of youths and young adults, who have received hate comments, have received these from unknown persons – either from strangers who are not anonymous (29%) or from anonymous persons (26%).
4
Mental distress
33 percent of those who received hateful comments state that they have poorer self-esteem/self-image due to the comments. More than twice as many girls (31%) as boys (14%) say the comments negatively affected them.
Researchers from Lancaster University in the UK and the University of California, Berkeley, have looked into people’s perceptions of fake faces created by artificial intelligence compared to real faces.
Three main findings:
1
Unable to differentiate
Artificial intelligence creates such realistic human faces that people can’t distinguish them from real faces. When asked to differentiate between synthetic faces and real ones, the participants did slightly worse than pure chance (48,2 percent correct answers).
2
Did not get better with training
The average accuracy improved slightly to 59 percent when the participants were trained to recognize computer-generated faces. Despite providing trial-by-trial feedback, there was no improvement in accuracy over time.
3
More trustworthy
Fake faces generated by AI are perceived as 7.7 percent more trustworthy, on average, than real faces. The researchers find this difference to be small but significant. Women are generally perceived as more reliable than men, and a smiling face is more likely to be rated as trustworthy.
How can social media platforms more effectively promote reliable information? New research indicates that the answer can be found by studying who the readers are.
Two main findings:
1
Popularity does not predict news reliability
Popular news content that algorithmic recommendations often highlight is not necessarily reliable. The popularity of a news source is at best weakly associated with its reliability.
2
Audience partisan diversity is a signal of reliable news
News sites with greater audience partisan diversity tend to have higher NewsGuard scores. In contrast, those with lower levels of diversity and correspondingly more homogeneous partisan audiences tend to have lower reliability scores. Thus, the researchers argue, partisan audience diversity is a valuable signal of higher journalistic standards – and this should be incorporated into algorithmic ranking decisions.
A study of more than 2,400 popular fake and real news websites show how fake news is funded through well-known legitimate ad networks.
Four main findings:
1
Direct advertising relationship
Google, IndexExchange, and AppNexus have a direct advertising relationship with more than 40 percent of fake news websites and a re-seller advertising relation with more than 60 percent of them.
2
Business and entertainment
The majority of advertisers on fake news websites come from the ‘Business’ category. Almost 40 percent display ads from ‘Entertainment’ websites. These ads contain captivating and, sometimes even click-bait, content from celebrity websites, television and movie programs, as well as entertainment news, tempting users.
3
Broad business operation
Entities who own fake news websites often also own (or operate) other types of websites for entertainment, business and politics, pointing to the fact that owning a fake news website is part of a broader business operation.
4
Aggressive tracking
Google, Facebook and Amazon are engaged in aggressive tracking in Fake News websites – much more aggressive than the tracking they do in the ‘General Web’.