Map
Videos
About
Under the hood
Contact
WORLD EMOTION GLOBAL TREND
WEAK
+0.5%
Tomorrow:
ANGRY
+2.9%
09/Nov/2016:
HAPPY
+1.7%
Last Data-set:
07/Nov/2016
05:13 UTC
▲
Daxian, China
sad
+23.8% − Lisburn, United Kingdom
strong
+19.9% − Waverley, United Kingdom
weak
+24.4% − Tarragona, Spain
strong
+21.8% − PANAMA, Panama
strong
+3.1% − ROAD TOWN, British Virgin Islands
confused
+22.0% − Zonguldak, Turkey
strong
+22.9% − Gurgaon, India
strong
+14.2% − Warren, United States
strong
+22.1% − Maiduguri, Nigeria
confused
+21.6% − Chillán, Chile
strong
+21.7% − BRIDGETOWN, Barbados
confused
+23.8% − Pocos de Caldas, Brazil
strong
+24.0% − Xichang, China
confused
+20.3% − Vallejo, United States
confused
+21.9% − Gurgaon, India
strong
+14.2% − Lubumbashi, Congo, Democratic Republic of the
sad
+19.0% − Bobo Dioulasso, Burkina Faso
angry
+20.4% − TIRANA, Albania
sad
+18.7% − Ubon Ratchathani, Thailand
confused
+23.5% − Fresno, United States
strong
+21.7% − Cardiff, United Kingdom
strong
+16.1% − Hamilton, Canada
confused
+21.0% − Arad, Romania
strong
+11.8% − Guilin, China
strong
+3.0% − Nizhnekamsk, Russia
confused
+21.0% − Jamalpur, Bangladesh
confused
+17.7% − Botou, China
strong
+24.2% − Baranovichi, Belarus
strong
+18.5% − Kofu, Japan
confused
+20.9% − Tyumen, Russia
strong
+7.1% − Zonguldak, Turkey
strong
+22.9% − Tameside, United Kingdom
confused
+19.1% − Springfield, United States
confused
+5.1% − Mulhouse, France
happy
+21.4% − Vadakara, India
sad
+6.6% − Engels, Russia
strong
+21.7% − Ulan-Ude, Russia
confused
+2.6% − Silay, Philippines
happy
+19.9% − Pegu, Myanmar
confused
+24.1% − Cangzhou, China
confused
+17.7% − Erlangen, Germany
confused
+22.9% − Diyarbakir, Turkey
strong
+22.7% − Laval, Canada
strong
+10.7% − Regensburg, Germany
strong
+16.0% − Kharagpur, India
strong
+17.6% − Medellín, Colombia
strong
+21.8% − The Wrekin, United Kingdom
happy
+23.6% − Tegal, Indonesia
confused
+4.6% − Phoenix, United States
strong
+11.7% − Pohang, Korea, South
confused
+21.8% − Ambala, India
happy
+21.8% − Paraná, Argentina
strong
+12.3% − BASSE-TERRE, Guadeloupe
strong
+24.8% − Monywa, Myanmar
confused
+22.1% − Rangpur, Bangladesh
happy
+24.3% − Surakarta, Indonesia
strong
+20.9% − Remscheid, Germany
strong
+19.6% − Ndola, Zambia
happy
+17.9% − Oberhausen, Germany
weak
+19.1% − Burgos, Spain
strong
+19.8% − Sedgemoor, United Kingdom
strong
+19.3% − The Wrekin, United Kingdom
happy
+23.6% − Beaumont, United States
confused
+12.1% − Fukuoka, Japan
weak
+13.4% − Waitakere, New Zealand
confused
+23.5% − Pinar del Río, Cuba
confused
+18.6% − Erbil, Iraq
strong
+20.1% − Tacoma, United States
confused
+20.3% − Guarapuava, Brazil
strong
+18.9% − Mönchengladbach, Germany
happy
+14.7% − Sikar, India
confused
+24.6% − Shaoyang, China
weak
+21.8% − Oberhausen, Germany
weak
+19.1% − Caruaru, Brazil
strong
+18.6% − LA HABANA, Cuba
strong
+18.2% − Engels, Russia
strong
+21.7% − Várzea Grande, Brazil
strong
+21.5% − Giza, Egypt
confused
+23.8% − Mbeya, Tanzania
confused
+22.8% − Jequié, Brazil
strong
+5.6% − Malabon, Philippines
happy
+23.0% − Gaya, India
strong
+23.6% − Loudi, China
weak
+17.8% − Yao, Japan
strong
+22.0% − Ulsan, Korea, South
confused
+24.5% − Lapu-Lapu, Philippines
strong
+24.6% − Remscheid, Germany
strong
+19.6% − Xichang, China
confused
+20.3% − Chungju, Korea, South
sad
+4.6% − Grodno, Belarus
sad
+19.8% − ST. GEORGES, Grenada
strong
+19.2% − Boksburg, South Africa
confused
+18.1% − Eastleigh, United Kingdom
happy
+19.0% − Kure, Japan
happy
+17.9% − Unnao, India
weak
+18.8% − Thai Nguyen, Vietnam
sad
+18.1% − Tacoma, United States
confused
+20.3% − Huntington Beach, United States
strong
+23.2% − BISHKEK, Kyrgyzstan
weak
+8.9% − Tanga, Tanzania
confused
+20.3% −
▼
Magdeburg, Germany
strong
-23.7% − Amagasaki, Japan
happy
-24.2% − Palakkad, India
strong
-17.6% − San Pablo, Philippines
strong
-18.3% − Tampa, United States
confused
-19.1% − Quezon City, Philippines
strong
-4.0% − Anand, India
strong
-3.1% − Kawachinagano, Japan
happy
-22.9% − NOUMEA, New Caledonia
strong
-18.8% − Alexandria, United States
strong
-11.9% − Halifax, Canada
strong
-19.1% − Rouen, France
strong
-6.3% − Muntinlupa, Philippines
strong
-19.8% − Chicago, United States
strong
-18.5% − Yingcheng, China
happy
-22.9% − Sapucaia, Brazil
strong
-18.8% − Darlington, United Kingdom
strong
-24.3% − Jiamusi, China
strong
-18.6% − Hampton, United States
strong
-12.1% − Jersey City, United States
strong
-23.2% − Brescia, Italy
strong
-18.6% − Dourados, Brazil
strong
-1.2% − Curitiba, Brazil
strong
-24.8% − Adana, Turkey
confused
-23.4% − Petrópolis, Brazil
strong
-18.6% − Tanjung Balai, Indonesia
weak
-4.9% − Valencia, Venezuela
confused
-8.0% − Sefton, United Kingdom
strong
-5.2% − Cochabamba, Bolivia
strong
-23.2% − Richmond, United States
confused
-21.8% − Geelong, Australia
confused
-2.1% − Gujrat, Pakistan
strong
-22.0% − Luohe, China
happy
-22.9% − Mojokerto, Indonesia
strong
-13.8% − Jinan, China
strong
-8.9% − San Jose, United States
confused
-24.0% − Chiba, Japan
strong
-24.8% − Serra, Brazil
strong
-5.4% − Sergiev Posad, Russia
happy
-17.8% − Crewe & Nantwich, United Kingdom
strong
-17.6% − Manchester, United Kingdom
strong
-9.2% − Kisumu, Kenya
confused
-19.7% − Peshawar, Pakistan
strong
-24.4% − Toluca, Mexico
confused
-22.6% − Nhatrang, Vietnam
happy
-22.9% − Batangas, Philippines
strong
-22.8% − Chimbote, Peru
strong
-22.8% − Birmingham, United States
confused
-22.6% − Ingolstadt, Germany
strong
-14.9% − Bareilly, India
confused
-23.5% − Gent, Belgium
strong
-4.2% − Iseyin, Nigeria
happy
-22.8% − Aguascalientes, Mexico
strong
-17.6% − Bridgeport, United States
strong
-18.9% − Leipzig, Germany
strong
-21.8% − Floridablanca, Colombia
strong
-22.9% − Richmond, United States
confused
-21.8% − Kochi, India
strong
-24.8% − Durango, Mexico
strong
-25.0% − South Cambridgeshire, United Kingdom
strong
-17.7% − Braila, Romania
strong
-17.5% − Fukuyama, Japan
strong
-22.7% − Sukabumi, Indonesia
happy
-9.2% − LISBON, Portugal
strong
-7.5% − Santiago de los Caballeros, Dominican Republic
confused
-18.9% − Teignbridge, United Kingdom
confused
-20.2% − Kotte, Sri Lanka
confused
-1.5% − Zaria, Nigeria
confused
-18.6% − Irving, United States
strong
-20.4% − MONROVIA, Liberia
happy
-23.4% − Kitchener, Canada
strong
-15.2% − Queimados, Brazil
strong
-20.4% −
=
Reggio di Calabria, Italy
happy
− Nasariya, Iraq
happy
− Sao Joao de Meriti, Brazil
happy
− Jastrzebie - Zdrój, Poland
confused
− Sidi-bel-Abbès, Algeria
happy
− Novocherkassk, Russia
happy
− Niiza, Japan
happy
− Bihar Sharif, India
happy
− Kurume, Japan
guilty
− Shaown, China
happy
− Xiaocan, China
happy
− Moji-Guaçu, Brazil
happy
− Pinxiang, China
happy
− Nandyal, India
happy
− Korla, China
strong
− Durg, India
weak
− San Fernando de Apure, Venezuela
strong
− Rubtsovsk, Russia
happy
− Sao José do Rio Prêto, Brazil
happy
− Evpatoriya, Ukraine
happy
− Jinin, China
happy
− Khouribga, Morocco
sad
− Lipetsk, Russia
strong
− Sirjan, Iran
happy
− Holon, Israel
confused
− Juazeiro do Norte, Brazil
happy
− Basingstoke & Deane, United Kingdom
happy
− Chinhae, Korea, South
happy
− Al-Rakka, Syrian Arab Republic
happy
− Calithèa, Greece
happy
− Deir El-Zor, Syrian Arab Republic
happy
− Kashihara, Japan
happy
− Shanwei, China
confused
− Colimas, Mexico
happy
− Taian, China
confused
− Mudangiang, China
happy
− Meizhou, China
strong
− Pórto Velho, Brazil
happy
− Shuangyashan, China
happy
− Kiselevsk, Russia
happy
− Alagoinhas, Brazil
strong
− Salamanca, Mexico
strong
− Changweon, Korea, South
happy
− Angren, Uzbekistan
confused
− Yuncheng, China
weak
− Dayuan, China
happy
− Ferraz de Vasconcelos, Brazil
happy
− Guangshui, China
happy
− Xuchang, China
happy
− Dlepmealow, South Africa
happy
− Guikong, China
happy
− Soyapango, El Salvador
happy
− Chongli, China
weak
− Taiyan, China
happy
− Debrezit, Ethiopia
happy
− Huaiyin, China
happy
− Syktivkar, Russia
happy
− Kadhimain, Iraq
happy
− Kanhangad, India
happy
− Taldikorgan, Kazakstan
happy
− Sialkote, Pakistan
happy
− Artux, China
happy
−
Reset - Show All Layers
Select a group to display an individual emotion layer:
happy
excited
overjoyed
thrilled
exuberant
ecstatic
weak
helpless
hopeless
beat
overwhelmed
impotent
confused
bewildered
trapped
troubled
desperate
lost
afraid
terrified
horrified
scared stiff
petrified
fearful
guilty
sorrowful
remorseful
ashamed
unworthy
worthless
sad
depressed
disappointed
alone
hurt
left out
strong
powerful
aggressive
gung ho
potent
super
angry
furious
enraged
outraged
aggravated
irate