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% − Kharagpur, India strong +17.6% − Xichang, China confused +20.3% − Remscheid, Germany strong +19.6% − Ambala, India happy +21.8% − Anyang, China confused +1.0% − Erbil, Iraq strong +20.1% − Hachinohe, Japan strong +21.2% − Raniganj, India confused +23.2% − Diyarbakir, Turkey strong +22.7% − Zonguldak, Turkey strong +22.9% − Giza, Egypt confused +23.8% − Várzea Grande, Brazil strong +21.5% − Fukuoka, Japan weak +13.4% − Botou, China strong +24.2% − Hamilton, Canada confused +21.0% − Cangzhou, China confused +17.7% − Ulsan, Korea, South confused +24.5% − Pocos de Caldas, Brazil strong +24.0% − Springfield, United States confused +5.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Lisburn, United Kingdom strong +19.9% − Botou, China strong +24.2% − Surakarta, Indonesia strong +20.9% − Tacoma, United States confused +20.3% − San Cristóbal, Venezuela weak +18.5% − Caruaru, Brazil strong +18.6% − Pegu, Myanmar confused +24.1% − Arad, Romania strong +11.8% − Piracicaba, Brazil strong +20.7% − Thai Nguyen, Vietnam sad +18.1% − Kure, Japan happy +17.9% − Monywa, Myanmar confused +22.1% − East Hampshire, United Kingdom confused +19.0% − Pohang, Korea, South confused +21.8% − BASSE-TERRE, Guadeloupe strong +24.8% − Tarragona, Spain strong +21.8% − Burgos, Spain strong +19.8% − Sikar, India confused +24.6% − Bobo Dioulasso, Burkina Faso angry +20.4% − The Wrekin, United Kingdom happy +23.6% − Chon Buri, Thailand strong +23.4% − Tacoma, United States confused +20.3% − Smolensk, Russia happy +17.6% − Susano, Brazil strong +1.7% − Waverley, United Kingdom weak +24.4% − Jamalpur, Bangladesh confused +17.7% − Medellín, Colombia strong +21.8% − Pinar del Río, Cuba confused +18.6% − Waitakere, New Zealand confused +23.5% − Yavatmal, India guilty +24.6% − Vallejo, United States confused +21.9% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Engels, Russia strong +21.7% − Ubon Ratchathani, Thailand confused +23.5% − Jhang, Pakistan strong +23.9% − Jhang, Pakistan strong +23.9% − Beaumont, United States confused +12.1% − Remscheid, Germany strong +19.6% − ST. GEORGES, Grenada strong +19.2% − Tangshan, China weak +22.3% − Lapu-Lapu, Philippines strong +24.6% − Tanga, Tanzania confused +20.3% − Loudi, China weak +17.8% − Kofu, Japan confused +20.9% − Erlangen, Germany confused +22.9% − Mulhouse, France happy +21.4% − Phoenix, United States strong +11.7% − Ulan-Ude, Russia confused +2.6% − Huntington Beach, United States strong +23.2% − Ichikawa, Japan strong +4.5% − Mbeya, Tanzania confused +22.8% − Abeokuta, Nigeria happy +19.5% − Gurgaon, India strong +14.2% − Amiens, France confused +22.5% − Oberhausen, Germany weak +19.1% − Rangpur, Bangladesh happy +24.3% − Unnao, India weak +18.8% − Chillán, Chile strong +21.7% − Cardiff, United Kingdom strong +16.1% − Chungju, Korea, South sad +4.6% − Boksburg, South Africa confused +18.1% − Paraná, Argentina strong +12.3% − Yao, Japan strong +22.0% − Tyumen, Russia strong +7.1% − BISHKEK, Kyrgyzstan weak +8.9% − PANAMA, Panama strong +3.1% − Xichang, China confused +20.3% − Ndola, Zambia happy +17.9% − Laval, Canada strong +10.7% − Maiduguri, Nigeria confused +21.6% − Vallejo, United States confused +21.9% − Tegal, Indonesia confused +4.6% − Nizhnekamsk, Russia confused +21.0% − Oberhausen, Germany weak +19.1% − Vadakara, India sad +6.6% − Guilin, China strong +3.0% − Abeokuta, Nigeria happy +19.5% − Shaoyang, China weak +21.8% − Chungju, Korea, South sad +4.6% − Silay, Philippines happy +19.9% −
Gent, Belgium strong -4.2% − Adana, Turkey confused -23.4% − Nhatrang, Vietnam happy -22.9% − Bareilly, India confused -23.5% − Palakkad, India strong -17.6% − Durango, Mexico strong -25.0% − Gujrat, Pakistan strong -22.0% − Amagasaki, Japan happy -24.2% − Peshawar, Pakistan strong -24.4% − Sukabumi, Indonesia happy -9.2% − Teignbridge, United Kingdom confused -20.2% − Manchester, United Kingdom strong -9.2% − Sergiev Posad, Russia happy -17.8% − NOUMEA, New Caledonia strong -18.8% − Kochi, India strong -24.8% − LISBON, Portugal strong -7.5% − Iseyin, Nigeria happy -22.8% − Zaria, Nigeria confused -18.6% − Richmond, United States confused -21.8% − Chicago, United States strong -18.5% − Petrópolis, Brazil strong -18.6% − Valencia, Venezuela confused -8.0% − Cochabamba, Bolivia strong -23.2% − Dourados, Brazil strong -1.2% − Floridablanca, Colombia strong -22.9% − Aguascalientes, Mexico strong -17.6% − Magdeburg, Germany strong -23.7% − Kitchener, Canada strong -15.2% − Rouen, France strong -6.3% − Irving, United States strong -20.4% − Ingolstadt, Germany strong -14.9% − Brescia, Italy strong -18.6% − Muntinlupa, Philippines strong -19.8% − Tampa, United States confused -19.1% − Bridgeport, United States strong -18.9% − Fukuyama, Japan strong -22.7% − Quezon City, Philippines strong -4.0% − Darlington, United Kingdom strong -24.3% − MONROVIA, Liberia happy -23.4% − Crewe & Nantwich, United Kingdom strong -17.6% − Sapucaia, Brazil strong -18.8% − Tanjung Balai, Indonesia weak -4.9% − Braila, Romania strong -17.5% − Serra, Brazil strong -5.4% − Halifax, Canada strong -19.1% − Yingcheng, China happy -22.9% − Mojokerto, Indonesia strong -13.8% − Jiamusi, China strong -18.6% − Richmond, United States confused -21.8% − Queimados, Brazil strong -20.4% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Hampton, United States strong -12.1% − Luohe, China happy -22.9% − Jersey City, United States strong -23.2% − Leipzig, Germany strong -21.8% − Chimbote, Peru strong -22.8% − Alexandria, United States strong -11.9% − Anand, India strong -3.1% − Toluca, Mexico confused -22.6% − Batangas, Philippines strong -22.8% − San Jose, United States confused -24.0% − Kotte, Sri Lanka confused -1.5% − Sefton, United Kingdom strong -5.2% − Chiba, Japan strong -24.8% − Curitiba, Brazil strong -24.8% − Jinan, China strong -8.9% − South Cambridgeshire, United Kingdom strong -17.7% − Kawachinagano, Japan happy -22.9% − Birmingham, United States confused -22.6% − Geelong, Australia confused -2.1% − Kisumu, Kenya confused -19.7% − San Pablo, Philippines strong -18.3% −
=
Angren, Uzbekistan confused − Sidi-bel-Abbès, Algeria happy − Dayuan, China happy − Guangshui, China happy − Shanwei, China confused − Sao Joao de Meriti, Brazil happy − Kiselevsk, Russia happy − Huaiyin, China happy − Holon, Israel confused − Nandyal, India happy − Yuncheng, China weak − Sirjan, Iran happy − Nasariya, Iraq happy − Niiza, Japan happy − Pórto Velho, Brazil happy − Basingstoke & Deane, United Kingdom happy − Taiyan, China happy − Dlepmealow, South Africa happy − Evpatoriya, Ukraine happy − Soyapango, El Salvador happy − Chinhae, Korea, South happy − Reggio di Calabria, Italy happy − Artux, China happy − Kurume, Japan guilty − Chongli, China weak − Rubtsovsk, Russia happy − Kashihara, Japan happy − Sialkote, Pakistan happy − Xuchang, China happy − Juazeiro do Norte, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Mudangiang, China happy − Guikong, China happy − Ferraz de Vasconcelos, Brazil happy − Changweon, Korea, South happy − Meizhou, China strong − Jastrzebie - Zdrój, Poland confused − Korla, China strong − Bihar Sharif, India happy − Deir El-Zor, Syrian Arab Republic happy − Taldikorgan, Kazakstan happy − Khouribga, Morocco sad − Kanhangad, India happy − Calithèa, Greece happy − Salamanca, Mexico strong − Shaown, China happy − Colimas, Mexico happy − Lipetsk, Russia strong − San Fernando de Apure, Venezuela strong − Sao José do Rio Prêto, Brazil happy − Moji-Guaçu, Brazil happy − Alagoinhas, Brazil strong − Novocherkassk, Russia happy − Kadhimain, Iraq happy − Xiaocan, China happy − Durg, India weak − Syktivkar, Russia happy − Taian, China confused − Pinxiang, China happy − Jinin, China happy − Debrezit, Ethiopia happy − Shuangyashan, China 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