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
Gaya, India strong +23.6% − Kure, Japan happy +17.9% − San Sebastián, Spain confused +24.0% − Kharagpur, India strong +17.6% − Piracicaba, Brazil strong +20.7% − Remscheid, Germany strong +19.6% − Anjo, Japan strong +2.2% − Waitakere, New Zealand confused +23.5% − Zonguldak, Turkey strong +22.9% − Guarapuava, Brazil strong +18.9% − San Cristóbal, Venezuela weak +18.5% − Sedgemoor, United Kingdom strong +19.3% − Silay, Philippines happy +19.9% − Thai Nguyen, Vietnam sad +18.1% − Vadakara, India sad +6.6% − BISHKEK, Kyrgyzstan weak +8.9% − East Hampshire, United Kingdom confused +19.0% − Smolensk, Russia happy +17.6% − Kofu, Japan confused +20.9% − Ndola, Zambia happy +17.9% − Chon Buri, Thailand strong +23.4% − Pocos de Caldas, Brazil strong +24.0% − Bobo Dioulasso, Burkina Faso angry +20.4% − Waverley, United Kingdom weak +24.4% − Regensburg, Germany strong +16.0% − Paraná, Argentina strong +12.3% − The Wrekin, United Kingdom happy +23.6% − Vallejo, United States confused +21.9% − Mulhouse, France happy +21.4% − The Wrekin, United Kingdom happy +23.6% − LA HABANA, Cuba strong +18.2% − La Spezia, Italy confused +22.0% − Tarragona, Spain strong +21.8% − Botou, China strong +24.2% − Engels, Russia strong +21.7% − Chillán, Chile strong +21.7% − Tangshan, China weak +22.3% − Erlangen, Germany confused +22.9% − Dunfermline, United Kingdom confused +6.9% − Ambala, India happy +21.8% − Ulsan, Korea, South confused +24.5% − Zonguldak, Turkey strong +22.9% − Gurgaon, India strong +14.2% − Monywa, Myanmar confused +22.1% − Botou, China strong +24.2% − Raniganj, India confused +23.2% − Jamalpur, Bangladesh confused +17.7% − Ichikawa, Japan strong +4.5% − ROAD TOWN, British Virgin Islands confused +22.0% − Unnao, India weak +18.8% − Lapu-Lapu, Philippines strong +24.6% − Xichang, China confused +20.3% − Jhang, Pakistan strong +23.9% − Malabon, Philippines happy +23.0% − Daxian, China sad +23.8% − Baranovichi, Belarus strong +18.5% − Abeokuta, Nigeria happy +19.5% − Vallejo, United States confused +21.9% − Fresno, United States strong +21.7% − Pinar del Río, Cuba confused +18.6% − Beaumont, United States confused +12.1% − Cardiff, United Kingdom strong +16.1% − Shaoyang, China weak +21.8% − Nizhnekamsk, Russia confused +21.0% − Tameside, United Kingdom confused +19.1% − Jhang, Pakistan strong +23.9% − Caruaru, Brazil strong +18.6% − Xichang, China confused +20.3% − Maiduguri, Nigeria confused +21.6% − Yao, Japan strong +22.0% − Gurgaon, India strong +14.2% − Tacoma, United States confused +20.3% − Abeokuta, Nigeria happy +19.5% − Surakarta, Indonesia strong +20.9% − Cangzhou, China confused +17.7% − Chungju, Korea, South sad +4.6% − Pinar del Río, Cuba confused +18.6% − Yokkaichi, Japan strong +19.6% − Warren, United States strong +22.1% − Huntington Beach, United States strong +23.2% − Grodno, Belarus sad +19.8% − Ulan-Ude, Russia confused +2.6% − Ubon Ratchathani, Thailand confused +23.5% − Susano, Brazil strong +1.7% − Remscheid, Germany strong +19.6% − Lisburn, United Kingdom strong +19.9% − Laval, Canada strong +10.7% − Phoenix, United States strong +11.7% − Anyang, China confused +1.0% − Diyarbakir, Turkey strong +22.7% − Tyumen, Russia strong +7.1% − Springfield, United States confused +5.1% − Rangpur, Bangladesh happy +24.3% − BRIDGETOWN, Barbados confused +23.8% − ST. GEORGES, Grenada strong +19.2% − Medellín, Colombia strong +21.8% − Pohang, Korea, South confused +21.8% − Eastleigh, United Kingdom happy +19.0% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − PANAMA, Panama strong +3.1% − Engels, Russia strong +21.7% −
Anand, India strong -3.1% − Dourados, Brazil strong -1.2% − Palakkad, India strong -17.6% − Gujrat, Pakistan strong -22.0% − Jiamusi, China strong -18.6% − Magdeburg, Germany strong -23.7% − Bareilly, India confused -23.5% − Manchester, United Kingdom strong -9.2% − Ingolstadt, Germany strong -14.9% − MONROVIA, Liberia happy -23.4% − Brescia, Italy strong -18.6% − Jinan, China strong -8.9% − Kotte, Sri Lanka confused -1.5% − Adana, Turkey confused -23.4% − Floridablanca, Colombia strong -22.9% − Chimbote, Peru strong -22.8% − Teignbridge, United Kingdom confused -20.2% − Kitchener, Canada strong -15.2% − Kochi, India strong -24.8% − Amagasaki, Japan happy -24.2% − Alexandria, United States strong -11.9% − Fukuyama, Japan strong -22.7% − Toluca, Mexico confused -22.6% − Sapucaia, Brazil strong -18.8% − Yingcheng, China happy -22.9% − Bridgeport, United States strong -18.9% − Batangas, Philippines strong -22.8% − Leipzig, Germany strong -21.8% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Muntinlupa, Philippines strong -19.8% − Valencia, Venezuela confused -8.0% − Serra, Brazil strong -5.4% − Hampton, United States strong -12.1% − Tanjung Balai, Indonesia weak -4.9% − Braila, Romania strong -17.5% − Richmond, United States confused -21.8% − Darlington, United Kingdom strong -24.3% − Geelong, Australia confused -2.1% − South Cambridgeshire, United Kingdom strong -17.7% − Richmond, United States confused -21.8% − Durango, Mexico strong -25.0% − Curitiba, Brazil strong -24.8% − Iseyin, Nigeria happy -22.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Tampa, United States confused -19.1% − Mojokerto, Indonesia strong -13.8% − Jersey City, United States strong -23.2% − Rouen, France strong -6.3% − Chicago, United States strong -18.5% − LISBON, Portugal strong -7.5% − Kisumu, Kenya confused -19.7% − San Pablo, Philippines strong -18.3% − Sukabumi, Indonesia happy -9.2% − Sergiev Posad, Russia happy -17.8% − Luohe, China happy -22.9% − Nhatrang, Vietnam happy -22.9% − Quezon City, Philippines strong -4.0% − NOUMEA, New Caledonia strong -18.8% − Chiba, Japan strong -24.8% − Sefton, United Kingdom strong -5.2% − Peshawar, Pakistan strong -24.4% − Birmingham, United States confused -22.6% − Gent, Belgium strong -4.2% − Irving, United States strong -20.4% − Cochabamba, Bolivia strong -23.2% − Kawachinagano, Japan happy -22.9% − Halifax, Canada strong -19.1% − Zaria, Nigeria confused -18.6% − Queimados, Brazil strong -20.4% − Petrópolis, Brazil strong -18.6% − Aguascalientes, Mexico strong -17.6% − San Jose, United States confused -24.0% −
=
Taian, China confused − Niiza, Japan happy − Changweon, Korea, South happy − Dayuan, China happy − Syktivkar, Russia happy − Durg, India weak − Shanwei, China confused − Dlepmealow, South Africa happy − Alagoinhas, Brazil strong − Jastrzebie - Zdrój, Poland confused − Sao Joao de Meriti, Brazil happy − Basingstoke & Deane, United Kingdom happy − Debrezit, Ethiopia happy − Xiaocan, China happy − Rubtsovsk, Russia happy − Shuangyashan, China happy − Evpatoriya, Ukraine happy − Korla, China strong − Xuchang, China happy − Pinxiang, China happy − Taldikorgan, Kazakstan happy − Holon, Israel confused − Juazeiro do Norte, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Colimas, Mexico happy − Novocherkassk, Russia happy − San Fernando de Apure, Venezuela strong − Yuncheng, China weak − Chongli, China weak − Lipetsk, Russia strong − Khouribga, Morocco sad − Reggio di Calabria, Italy happy − Shaown, China happy − Taiyan, China happy − Sao José do Rio Prêto, Brazil happy − Nasariya, Iraq happy − Pórto Velho, Brazil happy − Calithèa, Greece happy − Deir El-Zor, Syrian Arab Republic happy − Guikong, China happy − Jinin, China happy − Ferraz de Vasconcelos, Brazil happy − Chinhae, Korea, South happy − Sirjan, Iran happy − Sialkote, Pakistan happy − Soyapango, El Salvador happy − Artux, China happy − Meizhou, China strong − Angren, Uzbekistan confused − Moji-Guaçu, Brazil happy − Bihar Sharif, India happy − Huaiyin, China happy − Sidi-bel-Abbès, Algeria happy − Kadhimain, Iraq happy − Kashihara, Japan happy − Guangshui, China happy − Mudangiang, China happy − Salamanca, Mexico strong − Kanhangad, India happy − Kiselevsk, Russia happy − Nandyal, India happy − Kurume, Japan guilty
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