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
Medellín, Colombia strong +21.8% − Warren, United States strong +22.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Anyang, China confused +1.0% − Pocos de Caldas, Brazil strong +24.0% − Engels, Russia strong +21.7% − Sedgemoor, United Kingdom strong +19.3% − Giza, Egypt confused +23.8% − Tacoma, United States confused +20.3% − LA HABANA, Cuba strong +18.2% − Tarragona, Spain strong +21.8% − Malabon, Philippines happy +23.0% − Cardiff, United Kingdom strong +16.1% − Ubon Ratchathani, Thailand confused +23.5% − Remscheid, Germany strong +19.6% − Ndola, Zambia happy +17.9% − Huntington Beach, United States strong +23.2% − Yavatmal, India guilty +24.6% − Abeokuta, Nigeria happy +19.5% − Zonguldak, Turkey strong +22.9% − Dunfermline, United Kingdom confused +6.9% − Grodno, Belarus sad +19.8% − Hachinohe, Japan strong +21.2% − Silay, Philippines happy +19.9% − Yao, Japan strong +22.0% − Ulsan, Korea, South confused +24.5% − Vallejo, United States confused +21.9% − Anjo, Japan strong +2.2% − Amiens, France confused +22.5% − Monywa, Myanmar confused +22.1% − BASSE-TERRE, Guadeloupe strong +24.8% − Chillán, Chile strong +21.7% − Boksburg, South Africa confused +18.1% − La Spezia, Italy confused +22.0% − Raniganj, India confused +23.2% − Bobo Dioulasso, Burkina Faso angry +20.4% − Pinar del Río, Cuba confused +18.6% − Xichang, China confused +20.3% − Chungju, Korea, South sad +4.6% − Rangpur, Bangladesh happy +24.3% − Unnao, India weak +18.8% − San Cristóbal, Venezuela weak +18.5% − Botou, China strong +24.2% − Oberhausen, Germany weak +19.1% − Nizhnekamsk, Russia confused +21.0% − Yokkaichi, Japan strong +19.6% − Springfield, United States confused +5.1% − Guilin, China strong +3.0% − Lapu-Lapu, Philippines strong +24.6% − BRIDGETOWN, Barbados confused +23.8% − Abeokuta, Nigeria happy +19.5% − Smolensk, Russia happy +17.6% − Pegu, Myanmar confused +24.1% − Tegal, Indonesia confused +4.6% − Eastleigh, United Kingdom happy +19.0% − Daxian, China sad +23.8% − Diyarbakir, Turkey strong +22.7% − Ambala, India happy +21.8% − Ubon Ratchathani, Thailand confused +23.5% − Kure, Japan happy +17.9% − Gurgaon, India strong +14.2% − Tanga, Tanzania confused +20.3% − Jequié, Brazil strong +5.6% − PANAMA, Panama strong +3.1% − TIRANA, Albania sad +18.7% − North York, Canada strong +20.2% − Kharagpur, India strong +17.6% − Burgos, Spain strong +19.8% − Mulhouse, France happy +21.4% − Guarapuava, Brazil strong +18.9% − Maiduguri, Nigeria confused +21.6% − The Wrekin, United Kingdom happy +23.6% − Baranovichi, Belarus strong +18.5% − Oberhausen, Germany weak +19.1% − Erbil, Iraq strong +20.1% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Thai Nguyen, Vietnam sad +18.1% − Ichikawa, Japan strong +4.5% − Phoenix, United States strong +11.7% − Vadakara, India sad +6.6% − Arad, Romania strong +11.8% − Surakarta, Indonesia strong +20.9% − Loudi, China weak +17.8% − ST. GEORGES, Grenada strong +19.2% − Jamalpur, Bangladesh confused +17.7% − Tacoma, United States confused +20.3% − Hamilton, Canada confused +21.0% − The Wrekin, United Kingdom happy +23.6% − Xichang, China confused +20.3% − Sikar, India confused +24.6% − Waitakere, New Zealand confused +23.5% − Caruaru, Brazil strong +18.6% − Pohang, Korea, South confused +21.8% − Erlangen, Germany confused +22.9% − Shaoyang, China weak +21.8% − Botou, China strong +24.2% − Waverley, United Kingdom weak +24.4% − Engels, Russia strong +21.7% − Piracicaba, Brazil strong +20.7% − East Hampshire, United Kingdom confused +19.0% − Pinar del Río, Cuba confused +18.6% −
Geelong, Australia confused -2.1% − Floridablanca, Colombia strong -22.9% − Queimados, Brazil strong -20.4% − Cochabamba, Bolivia strong -23.2% − South Cambridgeshire, United Kingdom strong -17.7% − Tampa, United States confused -19.1% − Ingolstadt, Germany strong -14.9% − Muntinlupa, Philippines strong -19.8% − Petrópolis, Brazil strong -18.6% − Chiba, Japan strong -24.8% − Manchester, United Kingdom strong -9.2% − Luohe, China happy -22.9% − Durango, Mexico strong -25.0% − Adana, Turkey confused -23.4% − Sukabumi, Indonesia happy -9.2% − Batangas, Philippines strong -22.8% − Sapucaia, Brazil strong -18.8% − Serra, Brazil strong -5.4% − Alexandria, United States strong -11.9% − Tanjung Balai, Indonesia weak -4.9% − Magdeburg, Germany strong -23.7% − LISBON, Portugal strong -7.5% − Toluca, Mexico confused -22.6% − Richmond, United States confused -21.8% − San Jose, United States confused -24.0% − Crewe & Nantwich, United Kingdom strong -17.6% − Sergiev Posad, Russia happy -17.8% − Bridgeport, United States strong -18.9% − NOUMEA, New Caledonia strong -18.8% − Braila, Romania strong -17.5% − Dourados, Brazil strong -1.2% − Valencia, Venezuela confused -8.0% − Iseyin, Nigeria happy -22.8% − Darlington, United Kingdom strong -24.3% − San Pablo, Philippines strong -18.3% − Yingcheng, China happy -22.9% − Kitchener, Canada strong -15.2% − Teignbridge, United Kingdom confused -20.2% − Brescia, Italy strong -18.6% − Chicago, United States strong -18.5% − Rouen, France strong -6.3% − Richmond, United States confused -21.8% − Zaria, Nigeria confused -18.6% − Gujrat, Pakistan strong -22.0% − Irving, United States strong -20.4% − Mojokerto, Indonesia strong -13.8% − Kawachinagano, Japan happy -22.9% − Gent, Belgium strong -4.2% − Quezon City, Philippines strong -4.0% − Anand, India strong -3.1% − Chimbote, Peru strong -22.8% − Jinan, China strong -8.9% − Palakkad, India strong -17.6% − Kotte, Sri Lanka confused -1.5% − Curitiba, Brazil strong -24.8% − Jersey City, United States strong -23.2% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Bareilly, India confused -23.5% − Leipzig, Germany strong -21.8% − Hampton, United States strong -12.1% − Sefton, United Kingdom strong -5.2% − MONROVIA, Liberia happy -23.4% − Nhatrang, Vietnam happy -22.9% − Peshawar, Pakistan strong -24.4% − Kisumu, Kenya confused -19.7% − Fukuyama, Japan strong -22.7% − Kochi, India strong -24.8% − Jiamusi, China strong -18.6% − Birmingham, United States confused -22.6% − Aguascalientes, Mexico strong -17.6% − Halifax, Canada strong -19.1% − Amagasaki, Japan happy -24.2% −
=
Debrezit, Ethiopia happy − Reggio di Calabria, Italy happy − Shuangyashan, China happy − Taian, China confused − Meizhou, China strong − Nasariya, Iraq happy − Soyapango, El Salvador happy − Sao José do Rio Prêto, Brazil happy − Pórto Velho, Brazil happy − Dayuan, China happy − Shanwei, China confused − Guikong, China happy − Sirjan, Iran happy − Moji-Guaçu, Brazil happy − Taiyan, China happy − Sialkote, Pakistan happy − Chongli, China weak − Nandyal, India happy − Basingstoke & Deane, United Kingdom happy − Bihar Sharif, India happy − Guangshui, China happy − Kadhimain, Iraq happy − Al-Rakka, Syrian Arab Republic happy − Kurume, Japan guilty − Angren, Uzbekistan confused − Niiza, Japan happy − Calithèa, Greece happy − Sao Joao de Meriti, Brazil happy − Kanhangad, India happy − Xiaocan, China happy − Jastrzebie - Zdrój, Poland confused − Yuncheng, China weak − Alagoinhas, Brazil strong − Mudangiang, China happy − Deir El-Zor, Syrian Arab Republic happy − Xuchang, China happy − Khouribga, Morocco sad − Dlepmealow, South Africa happy − Syktivkar, Russia happy − Holon, Israel confused − Juazeiro do Norte, Brazil happy − Pinxiang, China happy − Korla, China strong − Ferraz de Vasconcelos, Brazil happy − Changweon, Korea, South happy − Evpatoriya, Ukraine happy − Durg, India weak − Novocherkassk, Russia happy − Jinin, China happy − Colimas, Mexico happy − Artux, China happy − Taldikorgan, Kazakstan happy − Lipetsk, Russia strong − Shaown, China happy − Salamanca, Mexico strong − Chinhae, Korea, South happy − Huaiyin, China happy − Kiselevsk, Russia happy − Kashihara, Japan happy − Rubtsovsk, Russia happy − Sidi-bel-Abbès, Algeria happy − San Fernando de Apure, Venezuela strong
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