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
Yokkaichi, Japan strong +19.6% − Abeokuta, Nigeria happy +19.5% − Giza, Egypt confused +23.8% − Waverley, United Kingdom weak +24.4% − Pinar del Río, Cuba confused +18.6% − Xichang, China confused +20.3% − Thai Nguyen, Vietnam sad +18.1% − Remscheid, Germany strong +19.6% − Baranovichi, Belarus strong +18.5% − Kofu, Japan confused +20.9% − Bobo Dioulasso, Burkina Faso angry +20.4% − Dunfermline, United Kingdom confused +6.9% − Grodno, Belarus sad +19.8% − Tacoma, United States confused +20.3% − Yavatmal, India guilty +24.6% − Diyarbakir, Turkey strong +22.7% − Pohang, Korea, South confused +21.8% − Botou, China strong +24.2% − Anjo, Japan strong +2.2% − Hachinohe, Japan strong +21.2% − East Hampshire, United Kingdom confused +19.0% − Ndola, Zambia happy +17.9% − Hamilton, Canada confused +21.0% − Tangshan, China weak +22.3% − Rangpur, Bangladesh happy +24.3% − Engels, Russia strong +21.7% − Pegu, Myanmar confused +24.1% − Huntington Beach, United States strong +23.2% − Oberhausen, Germany weak +19.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Springfield, United States confused +5.1% − Yao, Japan strong +22.0% − Daxian, China sad +23.8% − Pinar del Río, Cuba confused +18.6% − Ulsan, Korea, South confused +24.5% − Medellín, Colombia strong +21.8% − Burgos, Spain strong +19.8% − Zonguldak, Turkey strong +22.9% − The Wrekin, United Kingdom happy +23.6% − Zonguldak, Turkey strong +22.9% − Caruaru, Brazil strong +18.6% − Tanga, Tanzania confused +20.3% − PANAMA, Panama strong +3.1% − Lapu-Lapu, Philippines strong +24.6% − Ulan-Ude, Russia confused +2.6% − Raniganj, India confused +23.2% − Warren, United States strong +22.1% − Laval, Canada strong +10.7% − Chon Buri, Thailand strong +23.4% − Tegal, Indonesia confused +4.6% − Tacoma, United States confused +20.3% − LA HABANA, Cuba strong +18.2% − Xichang, China confused +20.3% − Gaya, India strong +23.6% − Mbeya, Tanzania confused +22.8% − Paraná, Argentina strong +12.3% − Kharagpur, India strong +17.6% − Erbil, Iraq strong +20.1% − San Cristóbal, Venezuela weak +18.5% − Phoenix, United States strong +11.7% − Ubon Ratchathani, Thailand confused +23.5% − Nizhnekamsk, Russia confused +21.0% − Engels, Russia strong +21.7% − The Wrekin, United Kingdom happy +23.6% − Malabon, Philippines happy +23.0% − Guilin, China strong +3.0% − BASSE-TERRE, Guadeloupe strong +24.8% − North York, Canada strong +20.2% − Regensburg, Germany strong +16.0% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Ubon Ratchathani, Thailand confused +23.5% − BISHKEK, Kyrgyzstan weak +8.9% − Várzea Grande, Brazil strong +21.5% − Vallejo, United States confused +21.9% − Silay, Philippines happy +19.9% − Mönchengladbach, Germany happy +14.7% − Tyumen, Russia strong +7.1% − Lisburn, United Kingdom strong +19.9% − BRIDGETOWN, Barbados confused +23.8% − Ambala, India happy +21.8% − Chungju, Korea, South sad +4.6% − Gurgaon, India strong +14.2% − La Spezia, Italy confused +22.0% − Amiens, France confused +22.5% − Remscheid, Germany strong +19.6% − Cardiff, United Kingdom strong +16.1% − Beaumont, United States confused +12.1% − Susano, Brazil strong +1.7% − Shaoyang, China weak +21.8% − Tarragona, Spain strong +21.8% − Abeokuta, Nigeria happy +19.5% − Piracicaba, Brazil strong +20.7% − San Sebastián, Spain confused +24.0% − Unnao, India weak +18.8% − Jamalpur, Bangladesh confused +17.7% − Smolensk, Russia happy +17.6% − Oberhausen, Germany weak +19.1% − Ichikawa, Japan strong +4.5% − Botou, China strong +24.2% − Chungju, Korea, South sad +4.6% − Cangzhou, China confused +17.7% −
Petrópolis, Brazil strong -18.6% − Halifax, Canada strong -19.1% − Crewe & Nantwich, United Kingdom strong -17.6% − San Pablo, Philippines strong -18.3% − Sapucaia, Brazil strong -18.8% − Jersey City, United States strong -23.2% − Floridablanca, Colombia strong -22.9% − Quezon City, Philippines strong -4.0% − Kotte, Sri Lanka confused -1.5% − Amagasaki, Japan happy -24.2% − Braila, Romania strong -17.5% − Aguascalientes, Mexico strong -17.6% − Gujrat, Pakistan strong -22.0% − Iseyin, Nigeria happy -22.8% − Luohe, China happy -22.9% − Fukuyama, Japan strong -22.7% − Nhatrang, Vietnam happy -22.9% − Adana, Turkey confused -23.4% − Kochi, India strong -24.8% − Sergiev Posad, Russia happy -17.8% − Magdeburg, Germany strong -23.7% − LISBON, Portugal strong -7.5% − Kitchener, Canada strong -15.2% − Cochabamba, Bolivia strong -23.2% − Zaria, Nigeria confused -18.6% − Dourados, Brazil strong -1.2% − Bridgeport, United States strong -18.9% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Richmond, United States confused -21.8% − Serra, Brazil strong -5.4% − Peshawar, Pakistan strong -24.4% − Kisumu, Kenya confused -19.7% − Brescia, Italy strong -18.6% − Toluca, Mexico confused -22.6% − Birmingham, United States confused -22.6% − Queimados, Brazil strong -20.4% − Richmond, United States confused -21.8% − Kawachinagano, Japan happy -22.9% − Geelong, Australia confused -2.1% − Sefton, United Kingdom strong -5.2% − Durango, Mexico strong -25.0% − Chiba, Japan strong -24.8% − Jiamusi, China strong -18.6% − Jinan, China strong -8.9% − Mojokerto, Indonesia strong -13.8% − Irving, United States strong -20.4% − Ingolstadt, Germany strong -14.9% − Manchester, United Kingdom strong -9.2% − Hampton, United States strong -12.1% − Curitiba, Brazil strong -24.8% − Bareilly, India confused -23.5% − Muntinlupa, Philippines strong -19.8% − Sukabumi, Indonesia happy -9.2% − Chimbote, Peru strong -22.8% − Tampa, United States confused -19.1% − Teignbridge, United Kingdom confused -20.2% − Alexandria, United States strong -11.9% − Batangas, Philippines strong -22.8% − Darlington, United Kingdom strong -24.3% − Anand, India strong -3.1% − Palakkad, India strong -17.6% − Yingcheng, China happy -22.9% − San Jose, United States confused -24.0% − Leipzig, Germany strong -21.8% − Gent, Belgium strong -4.2% − NOUMEA, New Caledonia strong -18.8% − Rouen, France strong -6.3% − MONROVIA, Liberia happy -23.4% − Chicago, United States strong -18.5% − Valencia, Venezuela confused -8.0% − Tanjung Balai, Indonesia weak -4.9% − South Cambridgeshire, United Kingdom strong -17.7% −
=
Pórto Velho, Brazil happy − Alagoinhas, Brazil strong − Xuchang, China happy − Calithèa, Greece happy − Niiza, Japan happy − Yuncheng, China weak − Taiyan, China happy − Sidi-bel-Abbès, Algeria happy − Debrezit, Ethiopia happy − Jinin, China happy − Guangshui, China happy − Changweon, Korea, South happy − Lipetsk, Russia strong − Taldikorgan, Kazakstan happy − Salamanca, Mexico strong − Pinxiang, China happy − Syktivkar, Russia happy − Jastrzebie - Zdrój, Poland confused − Sialkote, Pakistan happy − Shanwei, China confused − Kiselevsk, Russia happy − Rubtsovsk, Russia happy − Nasariya, Iraq happy − Basingstoke & Deane, United Kingdom happy − Kadhimain, Iraq happy − Chongli, China weak − Shaown, China happy − Ferraz de Vasconcelos, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Dlepmealow, South Africa happy − Taian, China confused − Sao José do Rio Prêto, Brazil happy − Novocherkassk, Russia happy − Holon, Israel confused − Xiaocan, China happy − Kurume, Japan guilty − Nandyal, India happy − Sirjan, Iran happy − Colimas, Mexico happy − Durg, India weak − Dayuan, China happy − Sao Joao de Meriti, Brazil happy − Angren, Uzbekistan confused − Guikong, China happy − Juazeiro do Norte, Brazil happy − Bihar Sharif, India happy − Korla, China strong − Soyapango, El Salvador happy − Chinhae, Korea, South happy − Shuangyashan, China happy − Khouribga, Morocco sad − Evpatoriya, Ukraine happy − Huaiyin, China happy − Meizhou, China strong − Reggio di Calabria, Italy happy − San Fernando de Apure, Venezuela strong − Moji-Guaçu, Brazil happy − Artux, China happy − Deir El-Zor, Syrian Arab Republic happy − Kanhangad, India happy − Mudangiang, China happy − Kashihara, Japan 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