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
The Wrekin, United Kingdom happy +23.6% − Yokkaichi, Japan strong +19.6% − North York, Canada strong +20.2% − Anyang, China confused +1.0% − Bobo Dioulasso, Burkina Faso angry +20.4% − Gurgaon, India strong +14.2% − Zonguldak, Turkey strong +22.9% − Burgos, Spain strong +19.8% − Ubon Ratchathani, Thailand confused +23.5% − BRIDGETOWN, Barbados confused +23.8% − Gurgaon, India strong +14.2% − East Hampshire, United Kingdom confused +19.0% − Tacoma, United States confused +20.3% − Chon Buri, Thailand strong +23.4% − Abeokuta, Nigeria happy +19.5% − Kharagpur, India strong +17.6% − Arad, Romania strong +11.8% − Loudi, China weak +17.8% − Giza, Egypt confused +23.8% − Erbil, Iraq strong +20.1% − Kure, Japan happy +17.9% − Jhang, Pakistan strong +23.9% − Lapu-Lapu, Philippines strong +24.6% − Ulan-Ude, Russia confused +2.6% − Pocos de Caldas, Brazil strong +24.0% − Tyumen, Russia strong +7.1% − Anjo, Japan strong +2.2% − Xichang, China confused +20.3% − San Cristóbal, Venezuela weak +18.5% − Baranovichi, Belarus strong +18.5% − Yao, Japan strong +22.0% − Raniganj, India confused +23.2% − Botou, China strong +24.2% − Chungju, Korea, South sad +4.6% − Cardiff, United Kingdom strong +16.1% − BASSE-TERRE, Guadeloupe strong +24.8% − Silay, Philippines happy +19.9% − Tanga, Tanzania confused +20.3% − Diyarbakir, Turkey strong +22.7% − Chungju, Korea, South sad +4.6% − Sikar, India confused +24.6% − Guilin, China strong +3.0% − San Sebastián, Spain confused +24.0% − Eastleigh, United Kingdom happy +19.0% − PANAMA, Panama strong +3.1% − Pinar del Río, Cuba confused +18.6% − Kofu, Japan confused +20.9% − ROAD TOWN, British Virgin Islands confused +22.0% − Beaumont, United States confused +12.1% − Medellín, Colombia strong +21.8% − Maiduguri, Nigeria confused +21.6% − Lisburn, United Kingdom strong +19.9% − LA HABANA, Cuba strong +18.2% − Monywa, Myanmar confused +22.1% − Chillán, Chile strong +21.7% − Várzea Grande, Brazil strong +21.5% − Cangzhou, China confused +17.7% − Mbeya, Tanzania confused +22.8% − Oberhausen, Germany weak +19.1% − Ulsan, Korea, South confused +24.5% − Unnao, India weak +18.8% − Laval, Canada strong +10.7% − Mönchengladbach, Germany happy +14.7% − Fukuoka, Japan weak +13.4% − Vallejo, United States confused +21.9% − Waitakere, New Zealand confused +23.5% − Sedgemoor, United Kingdom strong +19.3% − Ubon Ratchathani, Thailand confused +23.5% − Nizhnekamsk, Russia confused +21.0% − Malabon, Philippines happy +23.0% − Mulhouse, France happy +21.4% − Vadakara, India sad +6.6% − BISHKEK, Kyrgyzstan weak +8.9% − Boksburg, South Africa confused +18.1% − Remscheid, Germany strong +19.6% − Botou, China strong +24.2% − Smolensk, Russia happy +17.6% − Daxian, China sad +23.8% − Hachinohe, Japan strong +21.2% − Grodno, Belarus sad +19.8% − Regensburg, Germany strong +16.0% − La Spezia, Italy confused +22.0% − Piracicaba, Brazil strong +20.7% − Pinar del Río, Cuba confused +18.6% − Tangshan, China weak +22.3% − Ambala, India happy +21.8% − Vallejo, United States confused +21.9% − Amiens, France confused +22.5% − Waverley, United Kingdom weak +24.4% − Thai Nguyen, Vietnam sad +18.1% − Ichikawa, Japan strong +4.5% − Guarapuava, Brazil strong +18.9% − Zonguldak, Turkey strong +22.9% − Jequié, Brazil strong +5.6% − Engels, Russia strong +21.7% − Susano, Brazil strong +1.7% − Warren, United States strong +22.1% − Rangpur, Bangladesh happy +24.3% − Abeokuta, Nigeria happy +19.5% − Dunfermline, United Kingdom confused +6.9% − Jamalpur, Bangladesh confused +17.7% −
Serra, Brazil strong -5.4% − Magdeburg, Germany strong -23.7% − Leipzig, Germany strong -21.8% − Petrópolis, Brazil strong -18.6% − Muntinlupa, Philippines strong -19.8% − Tampa, United States confused -19.1% − Floridablanca, Colombia strong -22.9% − Batangas, Philippines strong -22.8% − Ingolstadt, Germany strong -14.9% − Sergiev Posad, Russia happy -17.8% − Jinan, China strong -8.9% − Luohe, China happy -22.9% − Braila, Romania strong -17.5% − Halifax, Canada strong -19.1% − Brescia, Italy strong -18.6% − Richmond, United States confused -21.8% − Gent, Belgium strong -4.2% − Iseyin, Nigeria happy -22.8% − Irving, United States strong -20.4% − Dourados, Brazil strong -1.2% − San Pablo, Philippines strong -18.3% − Adana, Turkey confused -23.4% − Aguascalientes, Mexico strong -17.6% − Manchester, United Kingdom strong -9.2% − Kotte, Sri Lanka confused -1.5% − Sukabumi, Indonesia happy -9.2% − Crewe & Nantwich, United Kingdom strong -17.6% − Sefton, United Kingdom strong -5.2% − Jiamusi, China strong -18.6% − Cochabamba, Bolivia strong -23.2% − Durango, Mexico strong -25.0% − Richmond, United States confused -21.8% − Curitiba, Brazil strong -24.8% − Zaria, Nigeria confused -18.6% − Mojokerto, Indonesia strong -13.8% − Fukuyama, Japan strong -22.7% − Peshawar, Pakistan strong -24.4% − Gujrat, Pakistan strong -22.0% − Chiba, Japan strong -24.8% − Geelong, Australia confused -2.1% − Kochi, India strong -24.8% − South Cambridgeshire, United Kingdom strong -17.7% − Alexandria, United States strong -11.9% − Palakkad, India strong -17.6% − Bareilly, India confused -23.5% − Kawachinagano, Japan happy -22.9% − Quezon City, Philippines strong -4.0% − Nhatrang, Vietnam happy -22.9% − Teignbridge, United Kingdom confused -20.2% − LISBON, Portugal strong -7.5% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Chicago, United States strong -18.5% − Chimbote, Peru strong -22.8% − Bridgeport, United States strong -18.9% − Anand, India strong -3.1% − Darlington, United Kingdom strong -24.3% − Jersey City, United States strong -23.2% − Kisumu, Kenya confused -19.7% − Birmingham, United States confused -22.6% − Hampton, United States strong -12.1% − NOUMEA, New Caledonia strong -18.8% − Rouen, France strong -6.3% − Tanjung Balai, Indonesia weak -4.9% − MONROVIA, Liberia happy -23.4% − Sapucaia, Brazil strong -18.8% − Yingcheng, China happy -22.9% − Amagasaki, Japan happy -24.2% − Kitchener, Canada strong -15.2% − Queimados, Brazil strong -20.4% − Toluca, Mexico confused -22.6% − San Jose, United States confused -24.0% − Valencia, Venezuela confused -8.0% −
=
Guangshui, China happy − Evpatoriya, Ukraine happy − Taian, China confused − Korla, China strong − Sirjan, Iran happy − Jinin, China happy − Dayuan, China happy − San Fernando de Apure, Venezuela strong − Kiselevsk, Russia happy − Reggio di Calabria, Italy happy − Kurume, Japan guilty − Shaown, China happy − Shanwei, China confused − Bihar Sharif, India happy − Novocherkassk, Russia happy − Rubtsovsk, Russia happy − Xiaocan, China happy − Holon, Israel confused − Sialkote, Pakistan happy − Salamanca, Mexico strong − Sao José do Rio Prêto, Brazil happy − Deir El-Zor, Syrian Arab Republic happy − Basingstoke & Deane, United Kingdom happy − Huaiyin, China happy − Nasariya, Iraq happy − Angren, Uzbekistan confused − Dlepmealow, South Africa happy − Xuchang, China happy − Debrezit, Ethiopia happy − Pórto Velho, Brazil happy − Khouribga, Morocco sad − Kadhimain, Iraq happy − Kanhangad, India happy − Nandyal, India happy − Colimas, Mexico happy − Mudangiang, China happy − Taldikorgan, Kazakstan happy − Niiza, Japan happy − Alagoinhas, Brazil strong − Al-Rakka, Syrian Arab Republic happy − Meizhou, China strong − Soyapango, El Salvador happy − Juazeiro do Norte, Brazil happy − Moji-Guaçu, Brazil happy − Changweon, Korea, South happy − Sidi-bel-Abbès, Algeria happy − Shuangyashan, China happy − Chinhae, Korea, South happy − Yuncheng, China weak − Chongli, China weak − Artux, China happy − Sao Joao de Meriti, Brazil happy − Taiyan, China happy − Kashihara, Japan happy − Calithèa, Greece happy − Durg, India weak − Jastrzebie - Zdrój, Poland confused − Lipetsk, Russia strong − Pinxiang, China happy − Guikong, China happy − Syktivkar, Russia happy − Ferraz de Vasconcelos, Brazil happy
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