Diversity

Published

February 12, 2026

AI summaries

Note that all the summary texts on this page are currently generated automatically using a Large Language Model (Google’s Gemini), based on the results tables and other information from the data. Therefore, please do not cite the verbal summary, but refer to the figures and tables for accurate information.

Demographics

Gender proportions (image)

Across short video posts published by news outlets globally, women made up an average of 34% of visible individuals. We observed variations across platforms; for instance, YouTube Shorts featured women in 29% of visible roles, which was significantly lower than Instagram’s 34%. TikTok had the highest share at 36%, but other platform differences were not statistically significant. Regarding outlet type, public broadcasters showed the highest representation of women at 37%, followed closely by digital outlets at 36%. Private broadcasters, however, displayed a significantly lower share of visible women at 32%, a 5 percentage point drop compared to digital outlets. Print outlets fell in the middle with 33%. Country-level analysis revealed substantial variation, ranging from lows of 24% in South Korea and 27% in Hungary and Poland, to highs of 46% in Norway, 42% in Romania and Sweden, and 41% in Finland.

Overall average

estimate p.value conf.low conf.high
0.34 0 0.32 0.36

Contrasts

term contrast estimate p.value conf.low conf.high
outlet_type Print - Digital -0.03 0.13 -0.08 0.01
outlet_type Private broadcaster - Digital -0.05 0.02 -0.09 -0.01
outlet_type Public broadcaster - Digital -0.01 0.81 -0.06 0.05
platform TikTok - Instagram 0.01 0.56 -0.02 0.03
platform YouTube Shorts - Instagram -0.04 0.00 -0.08 -0.01

Predictions by platform

platform estimate p.value conf.low conf.high
Instagram 0.34 0 0.32 0.37
TikTok 0.36 0 0.33 0.38
YouTube Shorts 0.29 0 0.26 0.31

Predictions by outlet type

outlet_type estimate p.value conf.low conf.high
Digital 0.36 0 0.32 0.40
Print 0.33 0 0.30 0.36
Private broadcaster 0.32 0 0.30 0.34
Public broadcaster 0.37 0 0.33 0.41

Predictions by country

country estimate p.value conf.low conf.high region
Argentina 0.32 0 0.30 0.34 Latin America
Australia 0.33 0 0.32 0.35 Asia-Pacific
Austria 0.36 0 0.34 0.38 Western Europe
Belgium 0.32 0 0.30 0.34 Western Europe
Brazil 0.33 0 0.32 0.35 Latin America
Bulgaria 0.33 0 0.31 0.34 Eastern Europe
Canada 0.35 0 0.33 0.37 North America
Chile 0.35 0 0.33 0.37 Latin America
Colombia 0.31 0 0.30 0.33 Latin America
Croatia 0.38 0 0.36 0.40 Southern Europe
Czech Republic 0.32 0 0.30 0.34 Eastern Europe
Denmark 0.37 0 0.35 0.39 Northern Europe
Finland 0.41 0 0.39 0.43 Northern Europe
France 0.31 0 0.29 0.32 Western Europe
Germany 0.36 0 0.34 0.37 Western Europe
Greece 0.37 0 0.36 0.39 Southern Europe
Hungary 0.27 0 0.25 0.28 Eastern Europe
India 0.28 0 0.27 0.30 Asia-Pacific
Indonesia 0.32 0 0.30 0.33 Asia-Pacific
Ireland 0.34 0 0.33 0.36 Northern Europe
Italy 0.32 0 0.30 0.34 Southern Europe
Japan 0.31 0 0.29 0.32 Asia-Pacific
Kenya 0.34 0 0.32 0.36 Africa
Malaysia 0.29 0 0.27 0.31 Asia-Pacific
Mexico 0.32 0 0.31 0.34 Latin America
Morocco 0.30 0 0.29 0.32 Africa
Netherlands 0.35 0 0.33 0.37 Western Europe
Nigeria 0.34 0 0.32 0.35 Africa
Norway 0.46 0 0.44 0.48 Northern Europe
Peru 0.32 0 0.30 0.33 Latin America
Philippines 0.39 0 0.37 0.40 Asia-Pacific
Poland 0.27 0 0.26 0.29 Eastern Europe
Portugal 0.38 0 0.36 0.40 Southern Europe
Romania 0.42 0 0.40 0.44 Eastern Europe
Singapore 0.32 0 0.31 0.34 Asia-Pacific
Slovakia 0.38 0 0.36 0.40 Eastern Europe
South Africa 0.33 0 0.31 0.35 Africa
South Korea 0.24 0 0.23 0.26 Asia-Pacific
Spain 0.33 0 0.31 0.35 Southern Europe
Sweden 0.42 0 0.40 0.44 Northern Europe
Switzerland 0.37 0 0.35 0.38 Western Europe
Taiwan 0.30 0 0.28 0.32 Asia-Pacific
Thailand 0.34 0 0.32 0.35 Asia-Pacific
Turkey 0.28 0 0.27 0.30 Southern Europe
United Kingdom 0.32 0 0.31 0.34 Northern Europe
United States 0.34 0 0.32 0.36 North America

Gender proportions (speech)

Across all short video posts published by news outlets, women spoke in an average of 41% of the video content. Differences in the share of women speaking across platforms were small and not statistically significant. However, looking at outlet types, private broadcasters featured women speaking in 39% of their videos, a significantly lower share compared to both digital outlets and public broadcasters, which each featured women in 43% of their videos. Print outlets showed women speaking in 41% of their videos, which was not significantly different from the other types. The representation of women speaking varied considerably by country, ranging from a low of 28% in Poland to a high of 56% in Norway, with Japan and Sweden also featuring women in 50% of their videos.

Overall average

estimate p.value conf.low conf.high
0.41 0 0.38 0.43

Contrasts

term contrast estimate p.value conf.low conf.high
outlet_type Print - Digital -0.05 0.07 -0.09 0.00
outlet_type Private broadcaster - Digital -0.06 0.02 -0.10 -0.01
outlet_type Public broadcaster - Digital -0.03 0.31 -0.09 0.03
platform TikTok - Instagram 0.02 0.12 -0.01 0.04
platform YouTube Shorts - Instagram 0.02 0.24 -0.01 0.05

Predictions by platform

platform estimate p.value conf.low conf.high
Instagram 0.39 0 0.36 0.41
TikTok 0.42 0 0.39 0.45
YouTube Shorts 0.42 0 0.38 0.45

Predictions by outlet type

outlet_type estimate p.value conf.low conf.high
Digital 0.43 0 0.39 0.48
Print 0.41 0 0.37 0.44
Private broadcaster 0.39 0 0.36 0.42
Public broadcaster 0.43 0 0.38 0.48

Predictions by country

country estimate p.value conf.low conf.high region
Argentina 0.37 0 0.35 0.40 Latin America
Australia 0.44 0 0.41 0.47 Asia-Pacific
Austria 0.42 0 0.40 0.45 Western Europe
Belgium 0.37 0 0.35 0.40 Western Europe
Brazil 0.39 0 0.36 0.41 Latin America
Bulgaria 0.39 0 0.37 0.42 Eastern Europe
Canada 0.41 0 0.38 0.43 North America
Chile 0.40 0 0.38 0.43 Latin America
Colombia 0.38 0 0.36 0.41 Latin America
Croatia 0.39 0 0.36 0.41 Southern Europe
Czech Republic 0.35 0 0.33 0.38 Eastern Europe
Denmark 0.32 0 0.30 0.34 Northern Europe
Finland 0.47 0 0.44 0.50 Northern Europe
France 0.43 0 0.41 0.46 Western Europe
Germany 0.45 0 0.43 0.48 Western Europe
Greece 0.37 0 0.35 0.40 Southern Europe
Hungary 0.33 0 0.31 0.35 Eastern Europe
India 0.35 0 0.32 0.37 Asia-Pacific
Indonesia 0.45 0 0.43 0.48 Asia-Pacific
Ireland 0.41 0 0.39 0.44 Northern Europe
Italy 0.34 0 0.32 0.36 Southern Europe
Japan 0.50 0 0.47 0.52 Asia-Pacific
Kenya 0.35 0 0.33 0.38 Africa
Malaysia 0.49 0 0.47 0.52 Asia-Pacific
Mexico 0.43 0 0.40 0.45 Latin America
Morocco 0.32 0 0.30 0.35 Africa
Netherlands 0.40 0 0.38 0.43 Western Europe
Nigeria 0.36 0 0.34 0.38 Africa
Norway 0.56 0 0.53 0.59 Northern Europe
Peru 0.38 0 0.35 0.40 Latin America
Philippines 0.47 0 0.44 0.49 Asia-Pacific
Poland 0.28 0 0.26 0.30 Eastern Europe
Portugal 0.44 0 0.42 0.47 Southern Europe
Romania 0.45 0 0.42 0.47 Eastern Europe
Singapore 0.39 0 0.36 0.41 Asia-Pacific
Slovakia 0.36 0 0.34 0.39 Eastern Europe
South Africa 0.44 0 0.41 0.46 Africa
South Korea 0.39 0 0.37 0.41 Asia-Pacific
Spain 0.36 0 0.34 0.39 Southern Europe
Sweden 0.50 0 0.47 0.52 Northern Europe
Switzerland 0.48 0 0.46 0.51 Western Europe
Taiwan 0.40 0 0.38 0.43 Asia-Pacific
Thailand 0.48 0 0.46 0.51 Asia-Pacific
Turkey 0.29 0 0.27 0.31 Southern Europe
United Kingdom 0.40 0 0.37 0.42 Northern Europe
United States 0.44 0 0.42 0.47 North America

Average person age

Across all platforms, news outlets worldwide featured individuals averaging 34 years old in their short video posts. Examining specific platforms, we observed that YouTube Shorts featured individuals with an average age of 35.1 years, which was significantly older than those on Instagram, averaging 34.1 years; TikTok videos featured individuals averaging 33.4 years. We found that differences in the average age of individuals across various outlet types—digital, print, private broadcaster, and public broadcaster—were minor and not statistically significant. A considerable variation emerged across countries, with the average age of persons featured ranging from as young as 29.5 years in Sweden and 30.0 years in Norway, to as old as 38.3 years in Poland and 37.5 years in Hungary.

Overall average

estimate p.value conf.low conf.high
33.96 0 33.32 34.6

Contrasts

term contrast estimate p.value conf.low conf.high
outlet_type Print - Digital 0.76 0.23 -0.47 1.99
outlet_type Private broadcaster - Digital 0.94 0.13 -0.27 2.15
outlet_type Public broadcaster - Digital 1.30 0.09 -0.22 2.82
platform TikTok - Instagram -0.49 0.07 -1.01 0.03
platform YouTube Shorts - Instagram 0.92 0.01 0.25 1.58

Predictions by platform

platform estimate p.value conf.low conf.high
Instagram 34.08 0 33.37 34.78
TikTok 33.39 0 32.69 34.08
YouTube Shorts 35.05 0 34.24 35.85

Predictions by outlet type

outlet_type estimate p.value conf.low conf.high
Digital 33.16 0 32.05 34.28
Print 33.73 0 32.87 34.59
Private broadcaster 34.41 0 33.58 35.25
Public broadcaster 33.91 0 32.67 35.15

Predictions by country

country estimate p.value conf.low conf.high region
Argentina 34.34 0 33.70 34.98 Latin America
Australia 34.48 0 33.84 35.12 Asia-Pacific
Austria 32.47 0 31.83 33.10 Western Europe
Belgium 34.32 0 33.68 34.96 Western Europe
Brazil 33.46 0 32.82 34.10 Latin America
Bulgaria 35.87 0 35.23 36.51 Eastern Europe
Canada 35.88 0 35.24 36.52 North America
Chile 35.94 0 35.30 36.58 Latin America
Colombia 33.94 0 33.30 34.58 Latin America
Croatia 33.82 0 33.18 34.46 Southern Europe
Czech Republic 34.34 0 33.70 34.98 Eastern Europe
Denmark 35.05 0 34.41 35.69 Northern Europe
Finland 31.61 0 30.97 32.25 Northern Europe
France 34.79 0 34.15 35.43 Western Europe
Germany 34.47 0 33.83 35.11 Western Europe
Greece 34.16 0 33.52 34.80 Southern Europe
Hungary 37.46 0 36.82 38.10 Eastern Europe
India 36.99 0 36.36 37.63 Asia-Pacific
Indonesia 31.52 0 30.88 32.16 Asia-Pacific
Ireland 34.76 0 34.12 35.40 Northern Europe
Italy 35.12 0 34.48 35.76 Southern Europe
Japan 34.00 0 33.36 34.64 Asia-Pacific
Kenya 31.03 0 30.39 31.67 Africa
Malaysia 32.87 0 32.23 33.51 Asia-Pacific
Mexico 35.98 0 35.34 36.61 Latin America
Morocco 34.70 0 34.06 35.34 Africa
Netherlands 33.44 0 32.80 34.08 Western Europe
Nigeria 33.63 0 32.99 34.27 Africa
Norway 29.99 0 29.36 30.63 Northern Europe
Peru 35.72 0 35.08 36.36 Latin America
Philippines 30.70 0 30.06 31.34 Asia-Pacific
Poland 38.25 0 37.61 38.89 Eastern Europe
Portugal 34.98 0 34.34 35.62 Southern Europe
Romania 31.34 0 30.70 31.98 Eastern Europe
Singapore 33.08 0 32.44 33.72 Asia-Pacific
Slovakia 33.06 0 32.42 33.70 Eastern Europe
South Africa 32.36 0 31.72 33.00 Africa
South Korea 34.96 0 34.32 35.60 Asia-Pacific
Spain 35.50 0 34.87 36.14 Southern Europe
Sweden 29.53 0 28.89 30.17 Northern Europe
Switzerland 31.52 0 30.88 32.16 Western Europe
Taiwan 32.68 0 32.05 33.32 Asia-Pacific
Thailand 31.16 0 30.52 31.80 Asia-Pacific
Turkey 37.06 0 36.42 37.70 Southern Europe
United Kingdom 35.61 0 34.98 36.25 Northern Europe
United States 33.47 0 32.84 34.11 North America

Age diversity

The overall average age diversity, measured by the interquartile range (IQR) of visible people’s ages in news video posts, was 13.8 years. While we observed slight variations, differences in age diversity across platforms like Instagram (14.1 years), TikTok (13.4 years), and YouTube Shorts (13.9 years) were small and not statistically significant. However, age diversity varied significantly depending on the type of news outlet. Private broadcasters presented videos with higher age diversity, averaging 14.2 years, which was a statistically significant 1.8 years greater than digital-native outlets, which averaged 12.7 years. Print outlets (13.7 years) and public broadcasters (14.3 years) showed age diversity comparable to private broadcasters, but no other significant contrasts were identified. Furthermore, age diversity varied considerably across countries, ranging from a low of 11.4 years in the Philippines to a high of 16.3 years in Poland.

Overall average

estimate p.value conf.low conf.high
13.79 0 13.12 14.45

Contrasts

term contrast estimate p.value conf.low conf.high
outlet_type Print - Digital 1.32 0.08 -0.16 2.80
outlet_type Private broadcaster - Digital 1.76 0.02 0.27 3.25
outlet_type Public broadcaster - Digital 1.74 0.07 -0.14 3.63
platform TikTok - Instagram -0.77 0.12 -1.74 0.19
platform YouTube Shorts - Instagram -0.40 0.46 -1.48 0.67

Predictions by platform

platform estimate p.value conf.low conf.high
Instagram 14.11 0 13.24 14.97
TikTok 13.39 0 12.53 14.26
YouTube Shorts 13.90 0 12.91 14.88

Predictions by outlet type

outlet_type estimate p.value conf.low conf.high
Digital 12.68 0 11.40 13.95
Print 13.74 0 12.77 14.70
Private broadcaster 14.22 0 13.23 15.21
Public broadcaster 14.30 0 12.78 15.82

Predictions by country

country estimate p.value conf.low conf.high region
Argentina 13.83 0 13.16 14.49 Latin America
Australia 15.57 0 14.90 16.23 Asia-Pacific
Austria 13.17 0 12.51 13.84 Western Europe
Belgium 12.08 0 11.42 12.75 Western Europe
Brazil 13.96 0 13.30 14.63 Latin America
Bulgaria 15.79 0 15.13 16.46 Eastern Europe
Canada 15.71 0 15.05 16.38 North America
Chile 15.79 0 15.12 16.45 Latin America
Colombia 12.09 0 11.42 12.75 Latin America
Croatia 15.27 0 14.60 15.93 Southern Europe
Czech Republic 14.94 0 14.28 15.61 Eastern Europe
Denmark 14.25 0 13.58 14.91 Northern Europe
Finland 13.67 0 13.00 14.33 Northern Europe
France 14.81 0 14.14 15.47 Western Europe
Germany 14.79 0 14.12 15.45 Western Europe
Greece 13.22 0 12.55 13.88 Southern Europe
Hungary 16.17 0 15.50 16.83 Eastern Europe
India 15.73 0 15.06 16.39 Asia-Pacific
Indonesia 11.55 0 10.88 12.21 Asia-Pacific
Ireland 14.52 0 13.85 15.18 Northern Europe
Italy 14.82 0 14.15 15.48 Southern Europe
Japan 13.78 0 13.12 14.45 Asia-Pacific
Kenya 12.11 0 11.44 12.77 Africa
Malaysia 12.09 0 11.42 12.75 Asia-Pacific
Mexico 14.81 0 14.14 15.48 Latin America
Morocco 13.30 0 12.63 13.97 Africa
Netherlands 13.30 0 12.63 13.96 Western Europe
Nigeria 12.93 0 12.26 13.59 Africa
Norway 11.79 0 11.12 12.45 Northern Europe
Peru 13.14 0 12.47 13.80 Latin America
Philippines 11.35 0 10.68 12.01 Asia-Pacific
Poland 16.31 0 15.64 16.97 Eastern Europe
Portugal 15.30 0 14.64 15.97 Southern Europe
Romania 11.70 0 11.04 12.37 Eastern Europe
Singapore 15.68 0 15.01 16.34 Asia-Pacific
Slovakia 13.54 0 12.87 14.20 Eastern Europe
South Africa 12.13 0 11.46 12.79 Africa
South Korea 13.67 0 13.00 14.33 Asia-Pacific
Spain 14.12 0 13.45 14.78 Southern Europe
Sweden 11.96 0 11.29 12.62 Northern Europe
Switzerland 12.03 0 11.36 12.69 Western Europe
Taiwan 13.25 0 12.59 13.92 Asia-Pacific
Thailand 12.75 0 12.08 13.41 Asia-Pacific
Turkey 12.42 0 11.75 13.08 Southern Europe
United Kingdom 16.11 0 15.44 16.77 Northern Europe
United States 13.89 0 13.23 14.56 North America

Content

For topical diversity, we estimated the effective number of topics per outlet-platform combination, based on our automatic topic classification with 19 news categories.

Topic diversity

News outlets globally covered an average of 6.6 distinct topics in their short video posts. We observed notable differences in topic diversity across platforms and outlet types. Instagram posts (7.1) displayed slightly greater topic diversity compared to TikTok posts (6.9), while YouTube Shorts (5.5) consistently showed substantially lower diversity than both other platforms. Regarding outlet types, private broadcasters (7.2) exhibited significantly higher topic diversity than digital outlets (6.1). Public broadcasters also demonstrated high diversity (7.4), while print outlets (6.0) and digital outlets had comparable, lower diversity. Topic diversity also varied considerably by country, ranging from a low of 5.0 in Turkey to a high of 8.2 in Singapore.

Overall average

estimate p.value conf.low conf.high
6.62 0 6.35 6.89

Contrasts

term contrast estimate p.value conf.low conf.high
outlet_type Print - Digital -0.18 0.57 -0.82 0.45
outlet_type Private broadcaster - Digital 1.22 0.00 0.58 1.87
outlet_type Public broadcaster - Digital 0.63 0.14 -0.20 1.45
platform Instagram - TikTok 0.35 0.04 0.01 0.69
platform YouTube Shorts - TikTok -1.54 0.00 -1.92 -1.17

Predictions by platform

platform estimate p.value conf.low conf.high
TikTok 6.92 0 6.58 7.25
Instagram 7.14 0 6.81 7.48
YouTube Shorts 5.47 0 5.09 5.85

Predictions by outlet type

outlet_type estimate p.value conf.low conf.high
Digital 6.14 0 5.59 6.69
Print 6.03 0 5.62 6.43
Private broadcaster 7.20 0 6.77 7.62
Public broadcaster 7.39 0 6.72 8.05

Predictions by country

country estimate p.value conf.low conf.high region
Argentina 7.28 0 7.01 7.55 Latin America
Australia 7.08 0 6.81 7.35 Asia-Pacific
Austria 6.80 0 6.53 7.07 Western Europe
Belgium 6.12 0 5.85 6.39 Western Europe
Brazil 5.96 0 5.69 6.23 Latin America
Bulgaria 6.50 0 6.23 6.77 Eastern Europe
Canada 6.61 0 6.34 6.88 North America
Chile 7.31 0 7.03 7.58 Latin America
Colombia 6.73 0 6.46 7.00 Latin America
Croatia 6.73 0 6.46 7.01 Southern Europe
Czech Republic 7.62 0 7.35 7.90 Eastern Europe
Denmark 6.82 0 6.55 7.09 Northern Europe
Finland 7.98 0 7.71 8.25 Northern Europe
France 7.12 0 6.85 7.39 Western Europe
Germany 6.03 0 5.76 6.30 Western Europe
Greece 6.03 0 5.76 6.30 Southern Europe
Hungary 5.34 0 5.07 5.61 Eastern Europe
India 7.04 0 6.77 7.31 Asia-Pacific
Indonesia 6.30 0 6.03 6.57 Asia-Pacific
Ireland 7.03 0 6.76 7.30 Northern Europe
Italy 6.22 0 5.94 6.49 Southern Europe
Japan 7.15 0 6.88 7.42 Asia-Pacific
Kenya 7.33 0 7.06 7.60 Africa
Malaysia 6.33 0 6.05 6.60 Asia-Pacific
Mexico 6.54 0 6.27 6.81 Latin America
Morocco 6.68 0 6.41 6.95 Africa
Netherlands 6.05 0 5.78 6.32 Western Europe
Nigeria 6.38 0 6.11 6.65 Africa
Norway 7.57 0 7.30 7.84 Northern Europe
Peru 6.63 0 6.36 6.90 Latin America
Philippines 5.92 0 5.65 6.19 Asia-Pacific
Poland 5.66 0 5.39 5.94 Eastern Europe
Portugal 7.25 0 6.98 7.52 Southern Europe
Romania 5.77 0 5.50 6.04 Eastern Europe
Singapore 8.17 0 7.90 8.44 Asia-Pacific
Slovakia 6.63 0 6.36 6.90 Eastern Europe
South Africa 6.23 0 5.96 6.50 Africa
South Korea 6.17 0 5.90 6.44 Asia-Pacific
Spain 6.60 0 6.33 6.87 Southern Europe
Sweden 7.39 0 7.12 7.66 Northern Europe
Switzerland 7.66 0 7.39 7.93 Western Europe
Taiwan 5.85 0 5.58 6.12 Asia-Pacific
Thailand 7.15 0 6.88 7.42 Asia-Pacific
Turkey 5.02 0 4.75 5.29 Southern Europe
United Kingdom 7.00 0 6.73 7.27 Northern Europe
United States 7.05 0 6.78 7.32 North America

Measures

We measured demographic diversity using the FairFace classifier (Kärkkäinen and Joo 2019), which classifies apparent gender, age group and ethnicity.

Topic diversity was estimated by computing the effective number of topics, which accounts for number of topics coded per outlet and their frequency distribution, see Laakso and Taagepera (1979) for a similar measure.

References

Kärkkäinen, Kimmo, and Jungseock Joo. 2019. “FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age.” https://doi.org/10.48550/ARXIV.1908.04913.
Laakso, Markku, and Rein Taagepera. 1979. ““Effective” Number of Parties.” Comparative Political Studies 12 (1): 3–27. https://doi.org/10.1177/001041407901200101.