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
Gurgaon, India strong +14.2% − Tarragona, Spain strong +21.8% − Ulan-Ude, Russia confused +2.6% − East Hampshire, United Kingdom confused +19.0% − Ambala, India happy +21.8% − Paraná, Argentina strong +12.3% − Lapu-Lapu, Philippines strong +24.6% − Silay, Philippines happy +19.9% − North York, Canada strong +20.2% − Remscheid, Germany strong +19.6% − Tanga, Tanzania confused +20.3% − Jhang, Pakistan strong +23.9% − ST. GEORGES, Grenada strong +19.2% − Thai Nguyen, Vietnam sad +18.1% − Mbeya, Tanzania confused +22.8% − PANAMA, Panama strong +3.1% − Ichikawa, Japan strong +4.5% − Vadakara, India sad +6.6% − Vallejo, United States confused +21.9% − Cangzhou, China confused +17.7% − Waitakere, New Zealand confused +23.5% − Tyumen, Russia strong +7.1% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Arad, Romania strong +11.8% − Tacoma, United States confused +20.3% − Phoenix, United States strong +11.7% − Botou, China strong +24.2% − Pocos de Caldas, Brazil strong +24.0% − San Cristóbal, Venezuela weak +18.5% − Ubon Ratchathani, Thailand confused +23.5% − Hamilton, Canada confused +21.0% − Chungju, Korea, South sad +4.6% − Malabon, Philippines happy +23.0% − Kure, Japan happy +17.9% − Nizhnekamsk, Russia confused +21.0% − TIRANA, Albania sad +18.7% − Monywa, Myanmar confused +22.1% − The Wrekin, United Kingdom happy +23.6% − Burgos, Spain strong +19.8% − Várzea Grande, Brazil strong +21.5% − BRIDGETOWN, Barbados confused +23.8% − Anyang, China confused +1.0% − Abeokuta, Nigeria happy +19.5% − Boksburg, South Africa confused +18.1% − Huntington Beach, United States strong +23.2% − Medellín, Colombia strong +21.8% − Pinar del Río, Cuba confused +18.6% − Smolensk, Russia happy +17.6% − Kharagpur, India strong +17.6% − Tegal, Indonesia confused +4.6% − Regensburg, Germany strong +16.0% − Pegu, Myanmar confused +24.1% − Raniganj, India confused +23.2% − Surakarta, Indonesia strong +20.9% − San Sebastián, Spain confused +24.0% − Baranovichi, Belarus strong +18.5% − ROAD TOWN, British Virgin Islands confused +22.0% − Piracicaba, Brazil strong +20.7% − Guarapuava, Brazil strong +18.9% − Gurgaon, India strong +14.2% − Grodno, Belarus sad +19.8% − Warren, United States strong +22.1% − Bobo Dioulasso, Burkina Faso angry +20.4% − Fukuoka, Japan weak +13.4% − Ulsan, Korea, South confused +24.5% − Diyarbakir, Turkey strong +22.7% − Chungju, Korea, South sad +4.6% − Fresno, United States strong +21.7% − Engels, Russia strong +21.7% − Cardiff, United Kingdom strong +16.1% − Laval, Canada strong +10.7% − Gaya, India strong +23.6% − Erbil, Iraq strong +20.1% − Yokkaichi, Japan strong +19.6% − Caruaru, Brazil strong +18.6% − Abeokuta, Nigeria happy +19.5% − Vallejo, United States confused +21.9% − Ubon Ratchathani, Thailand confused +23.5% − Dunfermline, United Kingdom confused +6.9% − Pohang, Korea, South confused +21.8% − Loudi, China weak +17.8% − BASSE-TERRE, Guadeloupe strong +24.8% − Jequié, Brazil strong +5.6% − Rangpur, Bangladesh happy +24.3% − Eastleigh, United Kingdom happy +19.0% − Engels, Russia strong +21.7% − Zonguldak, Turkey strong +22.9% − Tangshan, China weak +22.3% − Hachinohe, Japan strong +21.2% − Springfield, United States confused +5.1% − LA HABANA, Cuba strong +18.2% − Tacoma, United States confused +20.3% − Yavatmal, India guilty +24.6% − Shaoyang, China weak +21.8% − Jhang, Pakistan strong +23.9% − BISHKEK, Kyrgyzstan weak +8.9% − Remscheid, Germany strong +19.6% − Erlangen, Germany confused +22.9% − Lisburn, United Kingdom strong +19.9% − Waverley, United Kingdom weak +24.4% − Beaumont, United States confused +12.1% −
Kotte, Sri Lanka confused -1.5% − Richmond, United States confused -21.8% − Gent, Belgium strong -4.2% − Dourados, Brazil strong -1.2% − Aguascalientes, Mexico strong -17.6% − Quezon City, Philippines strong -4.0% − Peshawar, Pakistan strong -24.4% − Serra, Brazil strong -5.4% − Cochabamba, Bolivia strong -23.2% − Toluca, Mexico confused -22.6% − Tampa, United States confused -19.1% − Brescia, Italy strong -18.6% − Richmond, United States confused -21.8% − Petrópolis, Brazil strong -18.6% − Magdeburg, Germany strong -23.7% − Geelong, Australia confused -2.1% − Manchester, United Kingdom strong -9.2% − Rouen, France strong -6.3% − Birmingham, United States confused -22.6% − Crewe & Nantwich, United Kingdom strong -17.6% − Yingcheng, China happy -22.9% − LISBON, Portugal strong -7.5% − Jiamusi, China strong -18.6% − Halifax, Canada strong -19.1% − Irving, United States strong -20.4% − Braila, Romania strong -17.5% − Nhatrang, Vietnam happy -22.9% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Kochi, India strong -24.8% − Bridgeport, United States strong -18.9% − Darlington, United Kingdom strong -24.3% − Kawachinagano, Japan happy -22.9% − Chimbote, Peru strong -22.8% − Palakkad, India strong -17.6% − Leipzig, Germany strong -21.8% − Alexandria, United States strong -11.9% − Mojokerto, Indonesia strong -13.8% − MONROVIA, Liberia happy -23.4% − San Jose, United States confused -24.0% − Sefton, United Kingdom strong -5.2% − Durango, Mexico strong -25.0% − Fukuyama, Japan strong -22.7% − Iseyin, Nigeria happy -22.8% − Tanjung Balai, Indonesia weak -4.9% − NOUMEA, New Caledonia strong -18.8% − San Pablo, Philippines strong -18.3% − Sukabumi, Indonesia happy -9.2% − Jersey City, United States strong -23.2% − Chiba, Japan strong -24.8% − Ingolstadt, Germany strong -14.9% − Teignbridge, United Kingdom confused -20.2% − Gujrat, Pakistan strong -22.0% − Queimados, Brazil strong -20.4% − Sapucaia, Brazil strong -18.8% − Floridablanca, Colombia strong -22.9% − Curitiba, Brazil strong -24.8% − Hampton, United States strong -12.1% − Amagasaki, Japan happy -24.2% − South Cambridgeshire, United Kingdom strong -17.7% − Zaria, Nigeria confused -18.6% − Bareilly, India confused -23.5% − Jinan, China strong -8.9% − Batangas, Philippines strong -22.8% − Sergiev Posad, Russia happy -17.8% − Luohe, China happy -22.9% − Kisumu, Kenya confused -19.7% − Chicago, United States strong -18.5% − Anand, India strong -3.1% − Valencia, Venezuela confused -8.0% − Muntinlupa, Philippines strong -19.8% − Adana, Turkey confused -23.4% − Kitchener, Canada strong -15.2% −
=
Ferraz de Vasconcelos, Brazil happy − Taldikorgan, Kazakstan happy − Shuangyashan, China happy − Mudangiang, China happy − Kurume, Japan guilty − Al-Rakka, Syrian Arab Republic happy − Xuchang, China happy − Bihar Sharif, India happy − Colimas, Mexico happy − Moji-Guaçu, Brazil happy − Yuncheng, China weak − Kiselevsk, Russia happy − Debrezit, Ethiopia happy − Khouribga, Morocco sad − Soyapango, El Salvador happy − Reggio di Calabria, Italy happy − Salamanca, Mexico strong − Sao José do Rio Prêto, Brazil happy − Shaown, China happy − Durg, India weak − Niiza, Japan happy − Guikong, China happy − Basingstoke & Deane, United Kingdom happy − Korla, China strong − Jinin, China happy − Sirjan, Iran happy − Guangshui, China happy − San Fernando de Apure, Venezuela strong − Alagoinhas, Brazil strong − Chinhae, Korea, South happy − Rubtsovsk, Russia happy − Taiyan, China happy − Nandyal, India happy − Pórto Velho, Brazil happy − Dayuan, China happy − Huaiyin, China happy − Lipetsk, Russia strong − Changweon, Korea, South happy − Calithèa, Greece happy − Dlepmealow, South Africa happy − Kanhangad, India happy − Novocherkassk, Russia happy − Kadhimain, Iraq happy − Chongli, China weak − Sidi-bel-Abbès, Algeria happy − Meizhou, China strong − Kashihara, Japan happy − Nasariya, Iraq happy − Jastrzebie - Zdrój, Poland confused − Deir El-Zor, Syrian Arab Republic happy − Juazeiro do Norte, Brazil happy − Shanwei, China confused − Angren, Uzbekistan confused − Taian, China confused − Sao Joao de Meriti, Brazil happy − Holon, Israel confused − Artux, China happy − Evpatoriya, Ukraine happy − Syktivkar, Russia happy − Pinxiang, China happy − Xiaocan, China happy − Sialkote, Pakistan 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