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
Sedgemoor, United Kingdom strong +19.3% − Malabon, Philippines happy +23.0% − Chungju, Korea, South sad +4.6% − Lisburn, United Kingdom strong +19.9% − Huntington Beach, United States strong +23.2% − PANAMA, Panama strong +3.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Gaya, India strong +23.6% − Tangshan, China weak +22.3% − Beaumont, United States confused +12.1% − BASSE-TERRE, Guadeloupe strong +24.8% − Baranovichi, Belarus strong +18.5% − Springfield, United States confused +5.1% − Kharagpur, India strong +17.6% − Pinar del Río, Cuba confused +18.6% − Guarapuava, Brazil strong +18.9% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Anjo, Japan strong +2.2% − Ubon Ratchathani, Thailand confused +23.5% − Ndola, Zambia happy +17.9% − Waverley, United Kingdom weak +24.4% − Vallejo, United States confused +21.9% − Arad, Romania strong +11.8% − Caruaru, Brazil strong +18.6% − Tarragona, Spain strong +21.8% − Kure, Japan happy +17.9% − Chillán, Chile strong +21.7% − Tacoma, United States confused +20.3% − Remscheid, Germany strong +19.6% − Jamalpur, Bangladesh confused +17.7% − Jhang, Pakistan strong +23.9% − Bobo Dioulasso, Burkina Faso angry +20.4% − BISHKEK, Kyrgyzstan weak +8.9% − Pohang, Korea, South confused +21.8% − The Wrekin, United Kingdom happy +23.6% − Burgos, Spain strong +19.8% − Oberhausen, Germany weak +19.1% − Maiduguri, Nigeria confused +21.6% − Hamilton, Canada confused +21.0% − Daxian, China sad +23.8% − BRIDGETOWN, Barbados confused +23.8% − The Wrekin, United Kingdom happy +23.6% − San Sebastián, Spain confused +24.0% − Yokkaichi, Japan strong +19.6% − Chungju, Korea, South sad +4.6% − Monywa, Myanmar confused +22.1% − Piracicaba, Brazil strong +20.7% − Xichang, China confused +20.3% − Erlangen, Germany confused +22.9% − ST. GEORGES, Grenada strong +19.2% − Laval, Canada strong +10.7% − Silay, Philippines happy +19.9% − Cardiff, United Kingdom strong +16.1% − Raniganj, India confused +23.2% − Guilin, China strong +3.0% − Tameside, United Kingdom confused +19.1% − Lapu-Lapu, Philippines strong +24.6% − Nizhnekamsk, Russia confused +21.0% − Anyang, China confused +1.0% − Cangzhou, China confused +17.7% − Dunfermline, United Kingdom confused +6.9% − Engels, Russia strong +21.7% − Thai Nguyen, Vietnam sad +18.1% − Xichang, China confused +20.3% − Pocos de Caldas, Brazil strong +24.0% − Tacoma, United States confused +20.3% − Abeokuta, Nigeria happy +19.5% − Medellín, Colombia strong +21.8% − North York, Canada strong +20.2% − Ubon Ratchathani, Thailand confused +23.5% − Várzea Grande, Brazil strong +21.5% − Vadakara, India sad +6.6% − Warren, United States strong +22.1% − Mbeya, Tanzania confused +22.8% − Ambala, India happy +21.8% − Mönchengladbach, Germany happy +14.7% − Ulsan, Korea, South confused +24.5% − Tegal, Indonesia confused +4.6% − East Hampshire, United Kingdom confused +19.0% − San Cristóbal, Venezuela weak +18.5% − Yao, Japan strong +22.0% − Giza, Egypt confused +23.8% − Shaoyang, China weak +21.8% − Phoenix, United States strong +11.7% − Jhang, Pakistan strong +23.9% − La Spezia, Italy confused +22.0% − Remscheid, Germany strong +19.6% − Erbil, Iraq strong +20.1% − Chon Buri, Thailand strong +23.4% − Zonguldak, Turkey strong +22.9% − Botou, China strong +24.2% − Fukuoka, Japan weak +13.4% − Susano, Brazil strong +1.7% − Sikar, India confused +24.6% − Zonguldak, Turkey strong +22.9% − Regensburg, Germany strong +16.0% − Yavatmal, India guilty +24.6% − Ulan-Ude, Russia confused +2.6% − Tanga, Tanzania confused +20.3% − Abeokuta, Nigeria happy +19.5% − Eastleigh, United Kingdom happy +19.0% −
Richmond, United States confused -21.8% − South Cambridgeshire, United Kingdom strong -17.7% − Bridgeport, United States strong -18.9% − Kotte, Sri Lanka confused -1.5% − San Pablo, Philippines strong -18.3% − Alexandria, United States strong -11.9% − Richmond, United States confused -21.8% − Peshawar, Pakistan strong -24.4% − Muntinlupa, Philippines strong -19.8% − Petrópolis, Brazil strong -18.6% − Kitchener, Canada strong -15.2% − Sefton, United Kingdom strong -5.2% − Luohe, China happy -22.9% − Chicago, United States strong -18.5% − Irving, United States strong -20.4% − Batangas, Philippines strong -22.8% − Manchester, United Kingdom strong -9.2% − Jinan, China strong -8.9% − Birmingham, United States confused -22.6% − Serra, Brazil strong -5.4% − Aguascalientes, Mexico strong -17.6% − Toluca, Mexico confused -22.6% − Sergiev Posad, Russia happy -17.8% − Curitiba, Brazil strong -24.8% − Kochi, India strong -24.8% − Floridablanca, Colombia strong -22.9% − Magdeburg, Germany strong -23.7% − Rouen, France strong -6.3% − NOUMEA, New Caledonia strong -18.8% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Sukabumi, Indonesia happy -9.2% − Dourados, Brazil strong -1.2% − Braila, Romania strong -17.5% − San Jose, United States confused -24.0% − Kisumu, Kenya confused -19.7% − Geelong, Australia confused -2.1% − Quezon City, Philippines strong -4.0% − Jersey City, United States strong -23.2% − Chiba, Japan strong -24.8% − Adana, Turkey confused -23.4% − Gujrat, Pakistan strong -22.0% − Crewe & Nantwich, United Kingdom strong -17.6% − Leipzig, Germany strong -21.8% − MONROVIA, Liberia happy -23.4% − Bareilly, India confused -23.5% − Teignbridge, United Kingdom confused -20.2% − Queimados, Brazil strong -20.4% − Brescia, Italy strong -18.6% − Chimbote, Peru strong -22.8% − Sapucaia, Brazil strong -18.8% − Halifax, Canada strong -19.1% − Tanjung Balai, Indonesia weak -4.9% − Valencia, Venezuela confused -8.0% − Mojokerto, Indonesia strong -13.8% − Ingolstadt, Germany strong -14.9% − Amagasaki, Japan happy -24.2% − Kawachinagano, Japan happy -22.9% − Anand, India strong -3.1% − Nhatrang, Vietnam happy -22.9% − Durango, Mexico strong -25.0% − Jiamusi, China strong -18.6% − Iseyin, Nigeria happy -22.8% − Hampton, United States strong -12.1% − Gent, Belgium strong -4.2% − Darlington, United Kingdom strong -24.3% − Cochabamba, Bolivia strong -23.2% − Tampa, United States confused -19.1% − Fukuyama, Japan strong -22.7% − LISBON, Portugal strong -7.5% − Zaria, Nigeria confused -18.6% − Yingcheng, China happy -22.9% − Palakkad, India strong -17.6% −
=
Pórto Velho, Brazil happy − Deir El-Zor, Syrian Arab Republic happy − Salamanca, Mexico strong − Rubtsovsk, Russia happy − Shuangyashan, China happy − Kurume, Japan guilty − Nandyal, India happy − Jinin, China happy − Reggio di Calabria, Italy happy − San Fernando de Apure, Venezuela strong − Nasariya, Iraq happy − Sao Joao de Meriti, Brazil happy − Kadhimain, Iraq happy − Changweon, Korea, South happy − Xuchang, China happy − Artux, China happy − Lipetsk, Russia strong − Kashihara, Japan happy − Al-Rakka, Syrian Arab Republic happy − Mudangiang, China happy − Sialkote, Pakistan happy − Yuncheng, China weak − Sidi-bel-Abbès, Algeria happy − Guikong, China happy − Kanhangad, India happy − Bihar Sharif, India happy − Alagoinhas, Brazil strong − Chinhae, Korea, South happy − Novocherkassk, Russia happy − Colimas, Mexico happy − Jastrzebie - Zdrój, Poland confused − Basingstoke & Deane, United Kingdom happy − Sirjan, Iran happy − Huaiyin, China happy − Soyapango, El Salvador happy − Angren, Uzbekistan confused − Calithèa, Greece happy − Holon, Israel confused − Kiselevsk, Russia happy − Syktivkar, Russia happy − Pinxiang, China happy − Dayuan, China happy − Evpatoriya, Ukraine happy − Niiza, Japan happy − Moji-Guaçu, Brazil happy − Debrezit, Ethiopia happy − Korla, China strong − Xiaocan, China happy − Durg, India weak − Guangshui, China happy − Taiyan, China happy − Sao José do Rio Prêto, Brazil happy − Dlepmealow, South Africa happy − Meizhou, China strong − Shanwei, China confused − Taian, China confused − Khouribga, Morocco sad − Shaown, China happy − Ferraz de Vasconcelos, Brazil happy − Chongli, China weak − Taldikorgan, Kazakstan happy − Juazeiro do Norte, 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