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% − Cangzhou, China confused +17.7% − Gaya, India strong +23.6% − Diyarbakir, Turkey strong +22.7% − Gurgaon, India strong +14.2% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Pinar del Río, Cuba confused +18.6% − Caruaru, Brazil strong +18.6% − Grodno, Belarus sad +19.8% − Engels, Russia strong +21.7% − Zonguldak, Turkey strong +22.9% − BISHKEK, Kyrgyzstan weak +8.9% − Zonguldak, Turkey strong +22.9% − Rangpur, Bangladesh happy +24.3% − San Sebastián, Spain confused +24.0% − Cardiff, United Kingdom strong +16.1% − Piracicaba, Brazil strong +20.7% − Sedgemoor, United Kingdom strong +19.3% − Eastleigh, United Kingdom happy +19.0% − Tacoma, United States confused +20.3% − Boksburg, South Africa confused +18.1% − Chillán, Chile strong +21.7% − Paraná, Argentina strong +12.3% − Huntington Beach, United States strong +23.2% − Daxian, China sad +23.8% − Nizhnekamsk, Russia confused +21.0% − ROAD TOWN, British Virgin Islands confused +22.0% − Mönchengladbach, Germany happy +14.7% − Chungju, Korea, South sad +4.6% − Guarapuava, Brazil strong +18.9% − Beaumont, United States confused +12.1% − Pohang, Korea, South confused +21.8% − Tarragona, Spain strong +21.8% − Tegal, Indonesia confused +4.6% − Baranovichi, Belarus strong +18.5% − Hamilton, Canada confused +21.0% − Mulhouse, France happy +21.4% − Abeokuta, Nigeria happy +19.5% − Remscheid, Germany strong +19.6% − ST. GEORGES, Grenada strong +19.2% − Malabon, Philippines happy +23.0% − San Cristóbal, Venezuela weak +18.5% − Xichang, China confused +20.3% − Gurgaon, India strong +14.2% − Bobo Dioulasso, Burkina Faso angry +20.4% − Vallejo, United States confused +21.9% − Jequié, Brazil strong +5.6% − Laval, Canada strong +10.7% − Burgos, Spain strong +19.8% − TIRANA, Albania sad +18.7% − Engels, Russia strong +21.7% − Susano, Brazil strong +1.7% − Guilin, China strong +3.0% − East Hampshire, United Kingdom confused +19.0% − Waverley, United Kingdom weak +24.4% − Silay, Philippines happy +19.9% − Unnao, India weak +18.8% − Jamalpur, Bangladesh confused +17.7% − La Spezia, Italy confused +22.0% − Oberhausen, Germany weak +19.1% − Maiduguri, Nigeria confused +21.6% − Kharagpur, India strong +17.6% − Ulsan, Korea, South confused +24.5% − Tacoma, United States confused +20.3% − LA HABANA, Cuba strong +18.2% − Ichikawa, Japan strong +4.5% − Lisburn, United Kingdom strong +19.9% − Remscheid, Germany strong +19.6% − Anjo, Japan strong +2.2% − Oberhausen, Germany weak +19.1% − Raniganj, India confused +23.2% − Phoenix, United States strong +11.7% − Pinar del Río, Cuba confused +18.6% − Pegu, Myanmar confused +24.1% − Jhang, Pakistan strong +23.9% − Vadakara, India sad +6.6% − Fukuoka, Japan weak +13.4% − Chungju, Korea, South sad +4.6% − Ambala, India happy +21.8% − Loudi, China weak +17.8% − Chon Buri, Thailand strong +23.4% − Ubon Ratchathani, Thailand confused +23.5% − Smolensk, Russia happy +17.6% − Tyumen, Russia strong +7.1% − BRIDGETOWN, Barbados confused +23.8% − Xichang, China confused +20.3% − Dunfermline, United Kingdom confused +6.9% − Monywa, Myanmar confused +22.1% − PANAMA, Panama strong +3.1% − Arad, Romania strong +11.8% − Giza, Egypt confused +23.8% − Botou, China strong +24.2% − Thai Nguyen, Vietnam sad +18.1% − Ulan-Ude, Russia confused +2.6% − Ubon Ratchathani, Thailand confused +23.5% − North York, Canada strong +20.2% − Yavatmal, India guilty +24.6% − Kure, Japan happy +17.9% − BASSE-TERRE, Guadeloupe strong +24.8% − Regensburg, Germany strong +16.0% − Waitakere, New Zealand confused +23.5% −
Richmond, United States confused -21.8% − Kitchener, Canada strong -15.2% − Quezon City, Philippines strong -4.0% − Amagasaki, Japan happy -24.2% − San Pablo, Philippines strong -18.3% − Irving, United States strong -20.4% − Magdeburg, Germany strong -23.7% − Sefton, United Kingdom strong -5.2% − Iseyin, Nigeria happy -22.8% − South Cambridgeshire, United Kingdom strong -17.7% − Birmingham, United States confused -22.6% − Alexandria, United States strong -11.9% − Chiba, Japan strong -24.8% − Palakkad, India strong -17.6% − Nhatrang, Vietnam happy -22.9% − Sapucaia, Brazil strong -18.8% − Queimados, Brazil strong -20.4% − Zaria, Nigeria confused -18.6% − Fukuyama, Japan strong -22.7% − Ingolstadt, Germany strong -14.9% − Muntinlupa, Philippines strong -19.8% − Halifax, Canada strong -19.1% − Bareilly, India confused -23.5% − Anand, India strong -3.1% − Crewe & Nantwich, United Kingdom strong -17.6% − Mojokerto, Indonesia strong -13.8% − Kochi, India strong -24.8% − Batangas, Philippines strong -22.8% − Jinan, China strong -8.9% − Gent, Belgium strong -4.2% − Geelong, Australia confused -2.1% − Chicago, United States strong -18.5% − Rouen, France strong -6.3% − Tanjung Balai, Indonesia weak -4.9% − Kotte, Sri Lanka confused -1.5% − Bridgeport, United States strong -18.9% − Kawachinagano, Japan happy -22.9% − Cochabamba, Bolivia strong -23.2% − Tampa, United States confused -19.1% − Serra, Brazil strong -5.4% − Valencia, Venezuela confused -8.0% − Curitiba, Brazil strong -24.8% − Kisumu, Kenya confused -19.7% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Petrópolis, Brazil strong -18.6% − Darlington, United Kingdom strong -24.3% − Leipzig, Germany strong -21.8% − Sukabumi, Indonesia happy -9.2% − Gujrat, Pakistan strong -22.0% − Floridablanca, Colombia strong -22.9% − Teignbridge, United Kingdom confused -20.2% − Dourados, Brazil strong -1.2% − Luohe, China happy -22.9% − Toluca, Mexico confused -22.6% − Aguascalientes, Mexico strong -17.6% − Chimbote, Peru strong -22.8% − Jersey City, United States strong -23.2% − San Jose, United States confused -24.0% − NOUMEA, New Caledonia strong -18.8% − Adana, Turkey confused -23.4% − Sergiev Posad, Russia happy -17.8% − LISBON, Portugal strong -7.5% − Braila, Romania strong -17.5% − Peshawar, Pakistan strong -24.4% − Hampton, United States strong -12.1% − Jiamusi, China strong -18.6% − MONROVIA, Liberia happy -23.4% − Richmond, United States confused -21.8% − Brescia, Italy strong -18.6% − Yingcheng, China happy -22.9% − Manchester, United Kingdom strong -9.2% − Durango, Mexico strong -25.0% −
=
Sidi-bel-Abbès, Algeria happy − Reggio di Calabria, Italy happy − Dlepmealow, South Africa happy − Deir El-Zor, Syrian Arab Republic happy − Dayuan, China happy − Meizhou, China strong − Novocherkassk, Russia happy − Chongli, China weak − Shanwei, China confused − Sialkote, Pakistan happy − Taiyan, China happy − Kurume, Japan guilty − Jastrzebie - Zdrój, Poland confused − Xuchang, China happy − Kiselevsk, Russia happy − Nandyal, India happy − Shaown, China happy − Pinxiang, China happy − Changweon, Korea, South happy − Artux, China happy − Juazeiro do Norte, Brazil happy − Nasariya, Iraq happy − Holon, Israel confused − Bihar Sharif, India happy − Basingstoke & Deane, United Kingdom happy − Moji-Guaçu, Brazil happy − Salamanca, Mexico strong − Angren, Uzbekistan confused − Taldikorgan, Kazakstan happy − Guikong, China happy − Soyapango, El Salvador happy − Al-Rakka, Syrian Arab Republic happy − Sao Joao de Meriti, Brazil happy − Kadhimain, Iraq happy − San Fernando de Apure, Venezuela strong − Kanhangad, India happy − Evpatoriya, Ukraine happy − Lipetsk, Russia strong − Xiaocan, China happy − Pórto Velho, Brazil happy − Calithèa, Greece happy − Yuncheng, China weak − Kashihara, Japan happy − Sirjan, Iran happy − Guangshui, China happy − Niiza, Japan happy − Sao José do Rio Prêto, Brazil happy − Huaiyin, China happy − Korla, China strong − Ferraz de Vasconcelos, Brazil happy − Taian, China confused − Rubtsovsk, Russia happy − Mudangiang, China happy − Shuangyashan, China happy − Khouribga, Morocco sad − Durg, India weak − Jinin, China happy − Debrezit, Ethiopia happy − Alagoinhas, Brazil strong − Chinhae, Korea, South happy − Colimas, Mexico happy − Syktivkar, Russia 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