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% − Remscheid, Germany strong +19.6% − Kure, Japan happy +17.9% − Jequié, Brazil strong +5.6% − Jhang, Pakistan strong +23.9% − Jhang, Pakistan strong +23.9% − Vallejo, United States confused +21.9% − Surakarta, Indonesia strong +20.9% − Ambala, India happy +21.8% − Oberhausen, Germany weak +19.1% − Engels, Russia strong +21.7% − Abeokuta, Nigeria happy +19.5% − Sedgemoor, United Kingdom strong +19.3% − Tegal, Indonesia confused +4.6% − Yavatmal, India guilty +24.6% − Guilin, China strong +3.0% − Amiens, France confused +22.5% − Ulsan, Korea, South confused +24.5% − East Hampshire, United Kingdom confused +19.0% − Tangshan, China weak +22.3% − Susano, Brazil strong +1.7% − Bobo Dioulasso, Burkina Faso angry +20.4% − Fukuoka, Japan weak +13.4% − Raniganj, India confused +23.2% − Yao, Japan strong +22.0% − Ndola, Zambia happy +17.9% − Zonguldak, Turkey strong +22.9% − Erlangen, Germany confused +22.9% − Xichang, China confused +20.3% − Várzea Grande, Brazil strong +21.5% − Monywa, Myanmar confused +22.1% − Mbeya, Tanzania confused +22.8% − Pinar del Río, Cuba confused +18.6% − Huntington Beach, United States strong +23.2% − Silay, Philippines happy +19.9% − Thai Nguyen, Vietnam sad +18.1% − Tameside, United Kingdom confused +19.1% − Chon Buri, Thailand strong +23.4% − Gurgaon, India strong +14.2% − Tacoma, United States confused +20.3% − Chillán, Chile strong +21.7% − Loudi, China weak +17.8% − Unnao, India weak +18.8% − Vadakara, India sad +6.6% − Dunfermline, United Kingdom confused +6.9% − North York, Canada strong +20.2% − Waitakere, New Zealand confused +23.5% − Hachinohe, Japan strong +21.2% − Cardiff, United Kingdom strong +16.1% − The Wrekin, United Kingdom happy +23.6% − Jamalpur, Bangladesh confused +17.7% − Mönchengladbach, Germany happy +14.7% − Pegu, Myanmar confused +24.1% − Vallejo, United States confused +21.9% − Piracicaba, Brazil strong +20.7% − PANAMA, Panama strong +3.1% − Sikar, India confused +24.6% − Fresno, United States strong +21.7% − Ubon Ratchathani, Thailand confused +23.5% − Shaoyang, China weak +21.8% − Arad, Romania strong +11.8% − TIRANA, Albania sad +18.7% − Gurgaon, India strong +14.2% − San Cristóbal, Venezuela weak +18.5% − Lapu-Lapu, Philippines strong +24.6% − Zonguldak, Turkey strong +22.9% − Diyarbakir, Turkey strong +22.7% − Daxian, China sad +23.8% − BASSE-TERRE, Guadeloupe strong +24.8% − Baranovichi, Belarus strong +18.5% − Pocos de Caldas, Brazil strong +24.0% − Oberhausen, Germany weak +19.1% − Pinar del Río, Cuba confused +18.6% − Abeokuta, Nigeria happy +19.5% − Caruaru, Brazil strong +18.6% − Mulhouse, France happy +21.4% − Paraná, Argentina strong +12.3% − Kofu, Japan confused +20.9% − Boksburg, South Africa confused +18.1% − Springfield, United States confused +5.1% − Rangpur, Bangladesh happy +24.3% − Yokkaichi, Japan strong +19.6% − ST. GEORGES, Grenada strong +19.2% − La Spezia, Italy confused +22.0% − Medellín, Colombia strong +21.8% − Waverley, United Kingdom weak +24.4% − Kharagpur, India strong +17.6% − Guarapuava, Brazil strong +18.9% − Beaumont, United States confused +12.1% − Regensburg, Germany strong +16.0% − LA HABANA, Cuba strong +18.2% − Chungju, Korea, South sad +4.6% − Anjo, Japan strong +2.2% − San Sebastián, Spain confused +24.0% − Lisburn, United Kingdom strong +19.9% − Malabon, Philippines happy +23.0% − Botou, China strong +24.2% − Laval, Canada strong +10.7% − Eastleigh, United Kingdom happy +19.0% − Ubon Ratchathani, Thailand confused +23.5% − Cangzhou, China confused +17.7% −
Chiba, Japan strong -24.8% − Serra, Brazil strong -5.4% − NOUMEA, New Caledonia strong -18.8% − Iseyin, Nigeria happy -22.8% − Muntinlupa, Philippines strong -19.8% − Luohe, China happy -22.9% − Jiamusi, China strong -18.6% − Braila, Romania strong -17.5% − Palakkad, India strong -17.6% − Sukabumi, Indonesia happy -9.2% − Leipzig, Germany strong -21.8% − Manchester, United Kingdom strong -9.2% − Petrópolis, Brazil strong -18.6% − Irving, United States strong -20.4% − Zaria, Nigeria confused -18.6% − Cochabamba, Bolivia strong -23.2% − Gent, Belgium strong -4.2% − San Pablo, Philippines strong -18.3% − Jersey City, United States strong -23.2% − Rouen, France strong -6.3% − Toluca, Mexico confused -22.6% − Kitchener, Canada strong -15.2% − Richmond, United States confused -21.8% − South Cambridgeshire, United Kingdom strong -17.7% − Peshawar, Pakistan strong -24.4% − Kochi, India strong -24.8% − Richmond, United States confused -21.8% − Hampton, United States strong -12.1% − Batangas, Philippines strong -22.8% − Valencia, Venezuela confused -8.0% − Alexandria, United States strong -11.9% − Brescia, Italy strong -18.6% − LISBON, Portugal strong -7.5% − Birmingham, United States confused -22.6% − Aguascalientes, Mexico strong -17.6% − Jinan, China strong -8.9% − Adana, Turkey confused -23.4% − Darlington, United Kingdom strong -24.3% − Mojokerto, Indonesia strong -13.8% − Sefton, United Kingdom strong -5.2% − Bareilly, India confused -23.5% − Teignbridge, United Kingdom confused -20.2% − Fukuyama, Japan strong -22.7% − MONROVIA, Liberia happy -23.4% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Magdeburg, Germany strong -23.7% − Quezon City, Philippines strong -4.0% − Geelong, Australia confused -2.1% − Yingcheng, China happy -22.9% − Curitiba, Brazil strong -24.8% − Sergiev Posad, Russia happy -17.8% − Chimbote, Peru strong -22.8% − Anand, India strong -3.1% − Halifax, Canada strong -19.1% − Dourados, Brazil strong -1.2% − Crewe & Nantwich, United Kingdom strong -17.6% − Sapucaia, Brazil strong -18.8% − Durango, Mexico strong -25.0% − Gujrat, Pakistan strong -22.0% − Amagasaki, Japan happy -24.2% − Kisumu, Kenya confused -19.7% − Ingolstadt, Germany strong -14.9% − Kotte, Sri Lanka confused -1.5% − Kawachinagano, Japan happy -22.9% − Bridgeport, United States strong -18.9% − San Jose, United States confused -24.0% − Nhatrang, Vietnam happy -22.9% − Tanjung Balai, Indonesia weak -4.9% − Queimados, Brazil strong -20.4% − Tampa, United States confused -19.1% − Floridablanca, Colombia strong -22.9% − Chicago, United States strong -18.5% −
=
Rubtsovsk, Russia happy − Kiselevsk, Russia happy − Pórto Velho, Brazil happy − Dayuan, China happy − Dlepmealow, South Africa happy − Lipetsk, Russia strong − Xuchang, China happy − Holon, Israel confused − Changweon, Korea, South happy − Moji-Guaçu, Brazil happy − Guangshui, China happy − Shuangyashan, China happy − Kanhangad, India happy − Juazeiro do Norte, Brazil happy − Evpatoriya, Ukraine happy − Taian, China confused − Xiaocan, China happy − Salamanca, Mexico strong − Reggio di Calabria, Italy happy − Pinxiang, China happy − Sao Joao de Meriti, Brazil happy − San Fernando de Apure, Venezuela strong − Soyapango, El Salvador happy − Nandyal, India happy − Shanwei, China confused − Guikong, China happy − Novocherkassk, Russia happy − Mudangiang, China happy − Alagoinhas, Brazil strong − Kashihara, Japan happy − Sialkote, Pakistan happy − Jastrzebie - Zdrój, Poland confused − Sao José do Rio Prêto, Brazil happy − Meizhou, China strong − Nasariya, Iraq happy − Taldikorgan, Kazakstan happy − Bihar Sharif, India happy − Shaown, China happy − Kurume, Japan guilty − Sidi-bel-Abbès, Algeria happy − Korla, China strong − Huaiyin, China happy − Ferraz de Vasconcelos, Brazil happy − Basingstoke & Deane, United Kingdom happy − Deir El-Zor, Syrian Arab Republic happy − Colimas, Mexico happy − Durg, India weak − Al-Rakka, Syrian Arab Republic happy − Chinhae, Korea, South happy − Syktivkar, Russia happy − Angren, Uzbekistan confused − Niiza, Japan happy − Calithèa, Greece happy − Sirjan, Iran happy − Taiyan, China happy − Artux, China happy − Khouribga, Morocco sad − Debrezit, Ethiopia happy − Chongli, China weak − Jinin, China happy − Kadhimain, Iraq happy − Yuncheng, China weak
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