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
Hamilton, Canada confused +21.0% − Abeokuta, Nigeria happy +19.5% − Burgos, Spain strong +19.8% − Oberhausen, Germany weak +19.1% − Boksburg, South Africa confused +18.1% − Ubon Ratchathani, Thailand confused +23.5% − Jequié, Brazil strong +5.6% − San Cristóbal, Venezuela weak +18.5% − Engels, Russia strong +21.7% − Mbeya, Tanzania confused +22.8% − Unnao, India weak +18.8% − Guarapuava, Brazil strong +18.9% − Paraná, Argentina strong +12.3% − Maiduguri, Nigeria confused +21.6% − Pocos de Caldas, Brazil strong +24.0% − Nizhnekamsk, Russia confused +21.0% − Lapu-Lapu, Philippines strong +24.6% − Caruaru, Brazil strong +18.6% − Ulsan, Korea, South confused +24.5% − Oberhausen, Germany weak +19.1% − Chungju, Korea, South sad +4.6% − Várzea Grande, Brazil strong +21.5% − Xichang, China confused +20.3% − Ulan-Ude, Russia confused +2.6% − Erbil, Iraq strong +20.1% − Yao, Japan strong +22.0% − Jhang, Pakistan strong +23.9% − Daxian, China sad +23.8% − Loudi, China weak +17.8% − Vadakara, India sad +6.6% − Erlangen, Germany confused +22.9% − Lisburn, United Kingdom strong +19.9% − Kure, Japan happy +17.9% − Chillán, Chile strong +21.7% − Tanga, Tanzania confused +20.3% − Rangpur, Bangladesh happy +24.3% − Vallejo, United States confused +21.9% − Jhang, Pakistan strong +23.9% − The Wrekin, United Kingdom happy +23.6% − Ubon Ratchathani, Thailand confused +23.5% − Anyang, China confused +1.0% − Raniganj, India confused +23.2% − ROAD TOWN, British Virgin Islands confused +22.0% − LA HABANA, Cuba strong +18.2% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − The Wrekin, United Kingdom happy +23.6% − East Hampshire, United Kingdom confused +19.0% − Abeokuta, Nigeria happy +19.5% − Ichikawa, Japan strong +4.5% − San Sebastián, Spain confused +24.0% − Giza, Egypt confused +23.8% − Mönchengladbach, Germany happy +14.7% − PANAMA, Panama strong +3.1% − Baranovichi, Belarus strong +18.5% − Monywa, Myanmar confused +22.1% − Springfield, United States confused +5.1% − Yokkaichi, Japan strong +19.6% − Sedgemoor, United Kingdom strong +19.3% − Arad, Romania strong +11.8% − Medellín, Colombia strong +21.8% − Engels, Russia strong +21.7% − Pohang, Korea, South confused +21.8% − Smolensk, Russia happy +17.6% − Diyarbakir, Turkey strong +22.7% − Eastleigh, United Kingdom happy +19.0% − Remscheid, Germany strong +19.6% − Gurgaon, India strong +14.2% − Amiens, France confused +22.5% − Waitakere, New Zealand confused +23.5% − Piracicaba, Brazil strong +20.7% − Chungju, Korea, South sad +4.6% − Ambala, India happy +21.8% − La Spezia, Italy confused +22.0% − Regensburg, Germany strong +16.0% − Shaoyang, China weak +21.8% − Huntington Beach, United States strong +23.2% − Grodno, Belarus sad +19.8% − Tyumen, Russia strong +7.1% − Zonguldak, Turkey strong +22.9% − Tacoma, United States confused +20.3% − Tarragona, Spain strong +21.8% − Kofu, Japan confused +20.9% − Zonguldak, Turkey strong +22.9% − Kharagpur, India strong +17.6% − Chon Buri, Thailand strong +23.4% − Guilin, China strong +3.0% − Warren, United States strong +22.1% − Laval, Canada strong +10.7% − Beaumont, United States confused +12.1% − Silay, Philippines happy +19.9% − Fukuoka, Japan weak +13.4% − Ndola, Zambia happy +17.9% − Pinar del Río, Cuba confused +18.6% − Remscheid, Germany strong +19.6% − TIRANA, Albania sad +18.7% − Phoenix, United States strong +11.7% − Sikar, India confused +24.6% − Pinar del Río, Cuba confused +18.6% − Tangshan, China weak +22.3% − Tacoma, United States confused +20.3% − Bobo Dioulasso, Burkina Faso angry +20.4% −
Luohe, China happy -22.9% − Dourados, Brazil strong -1.2% − Muntinlupa, Philippines strong -19.8% − Queimados, Brazil strong -20.4% − Teignbridge, United Kingdom confused -20.2% − Amagasaki, Japan happy -24.2% − Braila, Romania strong -17.5% − Fukuyama, Japan strong -22.7% − Kitchener, Canada strong -15.2% − Zaria, Nigeria confused -18.6% − Darlington, United Kingdom strong -24.3% − Floridablanca, Colombia strong -22.9% − Durango, Mexico strong -25.0% − MONROVIA, Liberia happy -23.4% − Halifax, Canada strong -19.1% − Richmond, United States confused -21.8% − South Cambridgeshire, United Kingdom strong -17.7% − Birmingham, United States confused -22.6% − Serra, Brazil strong -5.4% − Cochabamba, Bolivia strong -23.2% − San Jose, United States confused -24.0% − Kochi, India strong -24.8% − NOUMEA, New Caledonia strong -18.8% − Alexandria, United States strong -11.9% − Sergiev Posad, Russia happy -17.8% − Sefton, United Kingdom strong -5.2% − Kawachinagano, Japan happy -22.9% − Magdeburg, Germany strong -23.7% − Kotte, Sri Lanka confused -1.5% − Batangas, Philippines strong -22.8% − Gent, Belgium strong -4.2% − Richmond, United States confused -21.8% − Geelong, Australia confused -2.1% − Rouen, France strong -6.3% − Mojokerto, Indonesia strong -13.8% − Manchester, United Kingdom strong -9.2% − Aguascalientes, Mexico strong -17.6% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Crewe & Nantwich, United Kingdom strong -17.6% − Bridgeport, United States strong -18.9% − Chimbote, Peru strong -22.8% − Valencia, Venezuela confused -8.0% − Curitiba, Brazil strong -24.8% − Tampa, United States confused -19.1% − LISBON, Portugal strong -7.5% − Adana, Turkey confused -23.4% − Petrópolis, Brazil strong -18.6% − Toluca, Mexico confused -22.6% − Leipzig, Germany strong -21.8% − Quezon City, Philippines strong -4.0% − Jiamusi, China strong -18.6% − Iseyin, Nigeria happy -22.8% − Bareilly, India confused -23.5% − Ingolstadt, Germany strong -14.9% − Sapucaia, Brazil strong -18.8% − Jersey City, United States strong -23.2% − Anand, India strong -3.1% − Sukabumi, Indonesia happy -9.2% − Irving, United States strong -20.4% − Jinan, China strong -8.9% − Brescia, Italy strong -18.6% − San Pablo, Philippines strong -18.3% − Nhatrang, Vietnam happy -22.9% − Tanjung Balai, Indonesia weak -4.9% − Chiba, Japan strong -24.8% − Peshawar, Pakistan strong -24.4% − Chicago, United States strong -18.5% − Palakkad, India strong -17.6% − Hampton, United States strong -12.1% − Gujrat, Pakistan strong -22.0% − Yingcheng, China happy -22.9% − Kisumu, Kenya confused -19.7% −
=
Rubtsovsk, Russia happy − Changweon, Korea, South happy − Colimas, Mexico happy − Nandyal, India happy − Chinhae, Korea, South happy − Deir El-Zor, Syrian Arab Republic happy − Huaiyin, China happy − Shaown, China happy − Guangshui, China happy − Calithèa, Greece happy − Nasariya, Iraq happy − Kadhimain, Iraq happy − Sao Joao de Meriti, Brazil happy − Taian, China confused − Jastrzebie - Zdrój, Poland confused − Durg, India weak − Angren, Uzbekistan confused − Juazeiro do Norte, Brazil happy − Basingstoke & Deane, United Kingdom happy − Sao José do Rio Prêto, Brazil happy − Taiyan, China happy − Meizhou, China strong − Shanwei, China confused − Reggio di Calabria, Italy happy − Khouribga, Morocco sad − San Fernando de Apure, Venezuela strong − Debrezit, Ethiopia happy − Syktivkar, Russia happy − Artux, China happy − Guikong, China happy − Sidi-bel-Abbès, Algeria happy − Novocherkassk, Russia happy − Pórto Velho, Brazil happy − Kiselevsk, Russia happy − Soyapango, El Salvador happy − Alagoinhas, Brazil strong − Dayuan, China happy − Moji-Guaçu, Brazil happy − Niiza, Japan happy − Evpatoriya, Ukraine happy − Chongli, China weak − Taldikorgan, Kazakstan happy − Xuchang, China happy − Kashihara, Japan happy − Sirjan, Iran happy − Yuncheng, China weak − Mudangiang, China happy − Al-Rakka, Syrian Arab Republic happy − Dlepmealow, South Africa happy − Holon, Israel confused − Salamanca, Mexico strong − Korla, China strong − Kanhangad, India happy − Bihar Sharif, India happy − Xiaocan, China happy − Sialkote, Pakistan happy − Shuangyashan, China happy − Lipetsk, Russia strong − Pinxiang, China happy − Kurume, Japan guilty − Ferraz de Vasconcelos, Brazil happy − Jinin, China 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