The most popular countries on Reddit
Countries with the most mentions
Here are the countries ranked by how many post titles mention them.
Rank | Country | Mentions |
---|---|---|
#1 | ![]() |
2,034,091 |
#2 | ![]() |
954,341 |
#3 | ![]() |
561,800 |
#4 | ![]() |
538,799 |
#5 | ![]() |
534,128 |
#6 | ![]() |
476,756 |
#7 | ![]() |
451,339 |
#8 | ![]() |
400,504 |
#9 | ![]() |
344,622 |
#10 | ![]() |
337,652 |
#11 | ![]() |
316,389 |
#12 | ![]() |
184,622 |
#13 | ![]() |
178,276 |
#14 | ![]() |
167,016 |
#15 | ![]() |
156,100 |
#16 | ![]() |
151,176 |
#17 | ![]() |
149,035 |
#18 | ![]() |
140,351 |
#19 | ![]() |
130,491 |
#20 | ![]() |
128,928 |
#21 | ![]() |
122,830 |
#22 | ![]() |
121,585 |
#23 | ![]() |
115,773 |
#24 | ![]() |
111,450 |
#25 | ![]() |
104,619 |
#26 | ![]() |
93,911 |
#27 | ![]() |
87,064 |
#28 | ![]() |
86,012 |
#29 | ![]() |
75,593 |
#30 | ![]() |
70,890 |
#31 | ![]() |
69,570 |
#32 | ![]() |
68,046 |
#33 | ![]() |
67,653 |
#34 | ![]() |
61,942 |
#35 | ![]() |
61,087 |
#36 | ![]() |
56,095 |
#37 | ![]() |
53,750 |
#38 | ![]() |
51,617 |
#39 | ![]() |
51,059 |
#40 | ![]() |
48,389 |
#41 | ![]() |
46,057 |
#42 | ![]() |
45,794 |
#43 | ![]() |
43,339 |
#44 | ![]() |
41,546 |
#45 | ![]() |
41,528 |
#46 | ![]() |
39,711 |
#47 | ![]() |
37,226 |
#48 | ![]() |
35,687 |
#49 | ![]() |
33,825 |
#50 | ![]() |
32,759 |
#51 | ![]() |
31,172 |
#52 | ![]() |
30,544 |
#53 | ![]() |
29,441 |
#54 | Palestinian Territory | 28,132 |
#55 | ![]() |
26,576 |
#56 | ![]() |
25,910 |
#57 | ![]() |
24,669 |
#58 | ![]() |
24,046 |
#59 | ![]() |
23,995 |
#60 | ![]() |
22,692 |
#61 | ![]() |
22,477 |
#62 | ![]() |
22,031 |
#63 | ![]() |
21,511 |
#64 | ![]() |
20,180 |
#65 | ![]() |
19,091 |
#66 | ![]() |
18,031 |
#67 | ![]() |
17,413 |
#68 | ![]() |
17,197 |
#69 | ![]() |
16,698 |
#70 | Serbia / Serbia and Montenegro | 16,674 |
#71 | ![]() |
16,518 |
#72 | ![]() |
16,501 |
#73 | ![]() |
16,269 |
#74 | ![]() |
15,333 |
#75 | ![]() |
14,296 |
#76 | ![]() |
13,780 |
#77 | ![]() |
13,730 |
#78 | ![]() |
13,165 |
#79 | ![]() |
12,779 |
#80 | ![]() |
12,312 |
#81 | ![]() |
12,282 |
#82 | Equatorial Guinea / Guinea | 12,239 |
#83 | ![]() |
12,213 |
#84 | ![]() |
11,914 |
#85 | ![]() |
11,426 |
#86 | ![]() |
11,226 |
#87 | ![]() |
11,071 |
#88 | ![]() |
10,998 |
#89 | ![]() |
10,996 |
#90 | ![]() |
10,897 |
#91 | ![]() |
10,887 |
#92 | ![]() |
10,802 |
#93 | ![]() |
10,685 |
#94 | ![]() |
10,664 |
#95 | ![]() |
10,592 |
#96 | ![]() |
10,065 |
#97 | ![]() |
9,691 |
#98 | ![]() |
9,111 |
#99 | ![]() |
9,059 |
#100 | ![]() |
9,058 |
#101 | ![]() |
8,518 |
#102 | ![]() |
8,505 |
#103 | ![]() |
8,272 |
#104 | ![]() |
8,248 |
#105 | ![]() |
7,805 |
#106 | ![]() |
7,507 |
#107 | ![]() |
7,451 |
#108 | ![]() |
7,305 |
#109 | ![]() |
7,226 |
#110 | ![]() |
7,198 |
#111 | ![]() |
7,187 |
#112 | ![]() |
7,175 |
#113 | ![]() |
6,966 |
#114 | ![]() |
6,888 |
#115 | ![]() |
6,759 |
#116 | ![]() |
6,502 |
#117 | ![]() |
6,411 |
#118 | ![]() |
6,400 |
#119 | ![]() |
6,225 |
#120 | ![]() |
5,916 |
#121 | ![]() |
5,786 |
#122 | ![]() |
5,661 |
#123 | ![]() |
5,540 |
#124 | ![]() |
5,348 |
#125 | ![]() |
5,279 |
#126 | ![]() |
5,279 |
#127 | ![]() |
5,001 |
#128 | ![]() |
4,923 |
#129 | ![]() |
4,832 |
#130 | ![]() |
4,741 |
#131 | ![]() |
4,678 |
#132 | ![]() |
4,065 |
#133 | ![]() |
4,058 |
#134 | ![]() |
4,000 |
#135 | ![]() |
3,946 |
#136 | ![]() |
3,905 |
#137 | ![]() |
3,640 |
#138 | ![]() |
3,588 |
#139 | ![]() |
3,584 |
#140 | ![]() |
3,580 |
#141 | ![]() |
3,307 |
#142 | ![]() |
3,238 |
#143 | ![]() |
3,089 |
#144 | ![]() |
2,986 |
#145 | ![]() |
2,862 |
#146 | ![]() |
2,829 |
#147 | ![]() |
2,772 |
#148 | ![]() |
2,716 |
#149 | ![]() |
2,548 |
#150 | ![]() |
2,520 |
#151 | ![]() |
2,520 |
#152 | ![]() |
2,333 |
#153 | ![]() |
2,329 |
#154 | ![]() |
2,289 |
#155 | ![]() |
2,198 |
#156 | ![]() |
2,156 |
#157 | ![]() |
1,997 |
#158 | ![]() |
1,909 |
#159 | ![]() |
1,853 |
#160 | ![]() |
1,825 |
#161 | ![]() |
1,822 |
#162 | ![]() |
1,679 |
#163 | ![]() |
1,638 |
#164 | ![]() |
1,617 |
#165 | ![]() |
1,602 |
#166 | ![]() |
1,596 |
#167 | ![]() |
1,522 |
Countries with the highest average scores
How about which countries have the highest average score per post? These countries are not just popular, but posts about them are well-liked as well.
Rank | Country | Mentions | Average score |
---|---|---|---|
#1 | ![]() |
12,312 | 68.93 |
#2 | ![]() |
39,711 | 56.44 |
#3 | ![]() |
87,064 | 52.87 |
#4 | ![]() |
1,596 | 49.76 |
#5 | ![]() |
43,339 | 48.26 |
#6 | ![]() |
3,584 | 47.45 |
#7 | ![]() |
1,825 | 46.46 |
#8 | ![]() |
2,329 | 45.92 |
#9 | ![]() |
1,617 | 45.72 |
#10 | ![]() |
9,059 | 45.21 |
#11 | ![]() |
7,451 | 45.10 |
#12 | ![]() |
61,087 | 43.87 |
#13 | ![]() |
61,942 | 41.74 |
#14 | ![]() |
130,491 | 41.04 |
#15 | ![]() |
344,622 | 40.64 |
#16 | ![]() |
6,400 | 40.20 |
#17 | ![]() |
17,197 | 38.85 |
#18 | ![]() |
68,046 | 38.75 |
#19 | ![]() |
2,862 | 38.65 |
#20 | ![]() |
70,890 | 37.99 |
#21 | ![]() |
10,887 | 37.99 |
#22 | ![]() |
111,450 | 37.88 |
#23 | ![]() |
69,570 | 37.83 |
#24 | Equatorial Guinea / Guinea | 12,239 | 37.76 |
#25 | ![]() |
13,165 | 37.13 |
#26 | ![]() |
2,289 | 36.96 |
#27 | ![]() |
10,592 | 36.81 |
#28 | ![]() |
5,786 | 36.16 |
#29 | ![]() |
10,897 | 35.65 |
#30 | ![]() |
451,339 | 35.34 |
#31 | ![]() |
10,802 | 35.27 |
#32 | ![]() |
46,057 | 34.88 |
#33 | ![]() |
6,502 | 34.83 |
#34 | ![]() |
16,501 | 34.75 |
#35 | ![]() |
4,058 | 34.15 |
#36 | ![]() |
22,031 | 34.01 |
#37 | ![]() |
7,305 | 33.94 |
#38 | ![]() |
2,520 | 33.93 |
#39 | ![]() |
11,226 | 33.85 |
#40 | ![]() |
20,180 | 33.14 |
#41 | ![]() |
184,622 | 33.07 |
#42 | ![]() |
6,888 | 32.67 |
#43 | ![]() |
6,966 | 32.53 |
#44 | ![]() |
12,779 | 32.48 |
#45 | ![]() |
167,016 | 32.42 |
#46 | ![]() |
337,652 | 32.20 |
#47 | ![]() |
21,511 | 32.04 |
#48 | ![]() |
10,664 | 32.03 |
#49 | ![]() |
37,226 | 31.72 |
#50 | ![]() |
31,172 | 31.69 |
#51 | ![]() |
33,825 | 31.59 |
#52 | ![]() |
476,756 | 31.36 |
#53 | ![]() |
13,780 | 30.97 |
#54 | ![]() |
400,504 | 30.88 |
#55 | ![]() |
149,035 | 30.85 |
#56 | ![]() |
6,411 | 30.81 |
#57 | ![]() |
8,272 | 30.59 |
#58 | ![]() |
11,426 | 30.52 |
#59 | ![]() |
534,128 | 30.42 |
#60 | ![]() |
5,540 | 29.76 |
#61 | ![]() |
7,198 | 29.73 |
#62 | ![]() |
121,585 | 29.38 |
#63 | ![]() |
4,000 | 29.30 |
#64 | ![]() |
1,909 | 29.15 |
#65 | ![]() |
25,910 | 29.10 |
#66 | ![]() |
23,995 | 28.89 |
#67 | ![]() |
15,333 | 28.60 |
#68 | ![]() |
151,176 | 28.24 |
#69 | ![]() |
22,477 | 27.93 |
#70 | ![]() |
9,691 | 27.61 |
#71 | ![]() |
16,698 | 27.48 |
#72 | ![]() |
12,213 | 27.42 |
#73 | ![]() |
3,946 | 27.34 |
#74 | ![]() |
2,829 | 27.26 |
#75 | ![]() |
10,998 | 27.03 |
#76 | ![]() |
140,351 | 27.00 |
#77 | ![]() |
3,640 | 26.96 |
#78 | ![]() |
3,238 | 26.74 |
#79 | ![]() |
128,928 | 26.54 |
#80 | ![]() |
7,175 | 26.23 |
#81 | ![]() |
561,800 | 26.15 |
#82 | ![]() |
29,441 | 25.92 |
#83 | ![]() |
4,832 | 25.86 |
#84 | ![]() |
75,593 | 25.84 |
#85 | ![]() |
5,001 | 25.73 |
#86 | ![]() |
16,518 | 25.61 |
#87 | ![]() |
45,794 | 25.48 |
#88 | Serbia / Serbia and Montenegro | 16,674 | 25.43 |
#89 | ![]() |
7,187 | 25.42 |
#90 | ![]() |
5,279 | 25.36 |
#91 | ![]() |
5,279 | 25.36 |
#92 | ![]() |
2,716 | 25.22 |
#93 | ![]() |
1,522 | 25.10 |
#94 | ![]() |
86,012 | 25.10 |
#95 | ![]() |
104,619 | 25.05 |
#96 | ![]() |
156,100 | 25.05 |
#97 | ![]() |
9,058 | 25.00 |
#98 | ![]() |
4,065 | 24.74 |
#99 | ![]() |
3,089 | 24.62 |
#100 | ![]() |
7,805 | 24.53 |
#101 | ![]() |
11,914 | 24.42 |
#102 | ![]() |
26,576 | 24.18 |
#103 | ![]() |
122,830 | 24.16 |
#104 | ![]() |
10,996 | 24.08 |
#105 | ![]() |
1,679 | 23.84 |
#106 | ![]() |
5,916 | 23.81 |
#107 | ![]() |
30,544 | 23.81 |
#108 | ![]() |
14,296 | 23.75 |
#109 | ![]() |
16,269 | 23.59 |
#110 | ![]() |
2,034,091 | 23.56 |
#111 | ![]() |
48,389 | 23.47 |
#112 | ![]() |
954,341 | 23.20 |
#113 | ![]() |
41,546 | 22.83 |
#114 | ![]() |
8,518 | 22.48 |
#115 | ![]() |
10,685 | 22.17 |
#116 | ![]() |
1,822 | 22.04 |
#117 | ![]() |
178,276 | 21.93 |
#118 | ![]() |
3,580 | 21.90 |
#119 | ![]() |
93,911 | 21.51 |
#120 | ![]() |
2,198 | 21.38 |
#121 | ![]() |
8,248 | 20.95 |
#122 | ![]() |
4,923 | 20.77 |
#123 | ![]() |
7,507 | 20.67 |
#124 | ![]() |
10,065 | 20.60 |
#125 | ![]() |
6,225 | 20.59 |
#126 | ![]() |
19,091 | 20.55 |
#127 | ![]() |
9,111 | 20.19 |
#128 | ![]() |
11,071 | 20.12 |
#129 | ![]() |
8,505 | 20.10 |
#130 | ![]() |
51,617 | 20.02 |
#131 | ![]() |
2,548 | 19.84 |
#132 | ![]() |
18,031 | 19.73 |
#133 | ![]() |
35,687 | 19.36 |
#134 | ![]() |
5,661 | 19.22 |
#135 | ![]() |
53,750 | 19.18 |
#136 | ![]() |
5,348 | 19.02 |
#137 | Palestinian Territory | 28,132 | 19.02 |
#138 | ![]() |
3,307 | 18.90 |
#139 | ![]() |
22,692 | 18.86 |
#140 | ![]() |
67,653 | 18.80 |
#141 | ![]() |
1,853 | 18.69 |
#142 | ![]() |
32,759 | 18.63 |
#143 | ![]() |
4,678 | 18.58 |
#144 | ![]() |
316,389 | 18.40 |
#145 | ![]() |
41,528 | 18.20 |
#146 | ![]() |
24,046 | 17.76 |
#147 | ![]() |
2,520 | 16.88 |
#148 | ![]() |
12,282 | 16.85 |
#149 | ![]() |
6,759 | 16.85 |
#150 | ![]() |
115,773 | 16.27 |
#151 | ![]() |
7,226 | 16.23 |
#152 | ![]() |
538,799 | 15.67 |
#153 | ![]() |
24,669 | 15.66 |
#154 | ![]() |
1,602 | 15.56 |
#155 | ![]() |
3,588 | 15.46 |
#156 | ![]() |
2,986 | 15.15 |
#157 | ![]() |
2,772 | 14.90 |
#158 | ![]() |
56,095 | 14.86 |
#159 | ![]() |
13,730 | 14.25 |
#160 | ![]() |
51,059 | 14.09 |
#161 | ![]() |
2,333 | 12.93 |
#162 | ![]() |
3,905 | 12.62 |
#163 | ![]() |
2,156 | 11.60 |
#164 | ![]() |
17,413 | 10.48 |
#165 | ![]() |
1,997 | 10.22 |
#166 | ![]() |
1,638 | 9.52 |
#167 | ![]() |
4,741 | 9.19 |
How I compiled the lists
I didn't do anything fancy here. If a post title has a word which matches the name of a country, I assume the post is related to that country. That causes some difficulties when there are homonyms, such as "Jordan" appearing in a post which is actually not talking about the country, but instead about Michael Jordan the computer scientist (or someone else with that name). Here is my whole mapping.
Instead of running this analysis on my own computer, I used Google BigQuery to find the names of countries in post titles. If you would like to learn how to run similar queries yourself, check out this great introduction to BigQuery analysis of Reddit.
The only fancy thing I did do is allowing multiple words to refer to the same country. For instance for "Germany" and "Japan", I also accept the demonyms "German" and "Japanese" in as well. For multi-word country names I also wanted to count abbreviations ("US", "U.S.", "USA", "U.S.A."). My query already removes dots, so it was enough to have "US", "USA" in the list. To prevent "US" from also matching "us", I decided to stick with case sensitivity.
I decided not to include "English" as a word for UK, because it more commonly refers to the language. Since it was ambiguous what "Korea" appearing along would refer to, I didn't count that as referring to anything unless it was preceded by "North" or "South".
By Bemmu, the guy behind Candy Japan.