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
Maiduguri, Nigeria confused +21.6% − Tyumen, Russia strong +7.1% − Vallejo, United States confused +21.9% − Silay, Philippines happy +19.9% − Hamilton, Canada confused +21.0% − Guarapuava, Brazil strong +18.9% − BASSE-TERRE, Guadeloupe strong +24.8% − Ulan-Ude, Russia confused +2.6% − BRIDGETOWN, Barbados confused +23.8% − San Cristóbal, Venezuela weak +18.5% − Gaya, India strong +23.6% − Laval, Canada strong +10.7% − Yao, Japan strong +22.0% − Tarragona, Spain strong +21.8% − Monywa, Myanmar confused +22.1% − Dunfermline, United Kingdom confused +6.9% − The Wrekin, United Kingdom happy +23.6% − Erbil, Iraq strong +20.1% − Hachinohe, Japan strong +21.2% − Smolensk, Russia happy +17.6% − Warren, United States strong +22.1% − Lapu-Lapu, Philippines strong +24.6% − Várzea Grande, Brazil strong +21.5% − Cardiff, United Kingdom strong +16.1% − Oberhausen, Germany weak +19.1% − Ubon Ratchathani, Thailand confused +23.5% − Thai Nguyen, Vietnam sad +18.1% − La Spezia, Italy confused +22.0% − Loudi, China weak +17.8% − Sedgemoor, United Kingdom strong +19.3% − Mbeya, Tanzania confused +22.8% − Fresno, United States strong +21.7% − Arad, Romania strong +11.8% − Ambala, India happy +21.8% − Guilin, China strong +3.0% − Botou, China strong +24.2% − Nizhnekamsk, Russia confused +21.0% − Tangshan, China weak +22.3% − Chon Buri, Thailand strong +23.4% − Jequié, Brazil strong +5.6% − Boksburg, South Africa confused +18.1% − San Sebastián, Spain confused +24.0% − Amiens, France confused +22.5% − Mönchengladbach, Germany happy +14.7% − Daxian, China sad +23.8% − Chillán, Chile strong +21.7% − Engels, Russia strong +21.7% − Pegu, Myanmar confused +24.1% − Cangzhou, China confused +17.7% − Vadakara, India sad +6.6% − Yavatmal, India guilty +24.6% − Jamalpur, Bangladesh confused +17.7% − Paraná, Argentina strong +12.3% − Tacoma, United States confused +20.3% − Gurgaon, India strong +14.2% − Rangpur, Bangladesh happy +24.3% − Beaumont, United States confused +12.1% − Mulhouse, France happy +21.4% − Jhang, Pakistan strong +23.9% − Tacoma, United States confused +20.3% − Botou, China strong +24.2% − Ndola, Zambia happy +17.9% − Lisburn, United Kingdom strong +19.9% − Giza, Egypt confused +23.8% − Kure, Japan happy +17.9% − Susano, Brazil strong +1.7% − Huntington Beach, United States strong +23.2% − Ulsan, Korea, South confused +24.5% − TIRANA, Albania sad +18.7% − Surakarta, Indonesia strong +20.9% − Abeokuta, Nigeria happy +19.5% − Malabon, Philippines happy +23.0% − Tameside, United Kingdom confused +19.1% − Gurgaon, India strong +14.2% − Kofu, Japan confused +20.9% − PANAMA, Panama strong +3.1% − Pocos de Caldas, Brazil strong +24.0% − Waitakere, New Zealand confused +23.5% − Eastleigh, United Kingdom happy +19.0% − Regensburg, Germany strong +16.0% − Zonguldak, Turkey strong +22.9% − Tanga, Tanzania confused +20.3% − Bobo Dioulasso, Burkina Faso angry +20.4% − Diyarbakir, Turkey strong +22.7% − Anyang, China confused +1.0% − Yokkaichi, Japan strong +19.6% − Remscheid, Germany strong +19.6% − Caruaru, Brazil strong +18.6% − LA HABANA, Cuba strong +18.2% − Pinar del Río, Cuba confused +18.6% − Fukuoka, Japan weak +13.4% − Springfield, United States confused +5.1% − Pohang, Korea, South confused +21.8% − Piracicaba, Brazil strong +20.7% − Zonguldak, Turkey strong +22.9% − Grodno, Belarus sad +19.8% − Xichang, China confused +20.3% − North York, Canada strong +20.2% − Burgos, Spain strong +19.8% − Medellín, Colombia strong +21.8% − Oberhausen, Germany weak +19.1% −
Amagasaki, Japan happy -24.2% − Luohe, China happy -22.9% − Gent, Belgium strong -4.2% − Petrópolis, Brazil strong -18.6% − Sukabumi, Indonesia happy -9.2% − Jersey City, United States strong -23.2% − Manchester, United Kingdom strong -9.2% − Sergiev Posad, Russia happy -17.8% − Birmingham, United States confused -22.6% − Cochabamba, Bolivia strong -23.2% − Queimados, Brazil strong -20.4% − Tanjung Balai, Indonesia weak -4.9% − Zaria, Nigeria confused -18.6% − Floridablanca, Colombia strong -22.9% − Tampa, United States confused -19.1% − Batangas, Philippines strong -22.8% − Irving, United States strong -20.4% − Hampton, United States strong -12.1% − Leipzig, Germany strong -21.8% − Kochi, India strong -24.8% − MONROVIA, Liberia happy -23.4% − Sapucaia, Brazil strong -18.8% − Ingolstadt, Germany strong -14.9% − Curitiba, Brazil strong -24.8% − Dourados, Brazil strong -1.2% − Mojokerto, Indonesia strong -13.8% − Fukuyama, Japan strong -22.7% − Richmond, United States confused -21.8% − Alexandria, United States strong -11.9% − Gujrat, Pakistan strong -22.0% − Teignbridge, United Kingdom confused -20.2% − Magdeburg, Germany strong -23.7% − Jiamusi, China strong -18.6% − Serra, Brazil strong -5.4% − NOUMEA, New Caledonia strong -18.8% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Darlington, United Kingdom strong -24.3% − Brescia, Italy strong -18.6% − Yingcheng, China happy -22.9% − Toluca, Mexico confused -22.6% − Palakkad, India strong -17.6% − Chicago, United States strong -18.5% − Sefton, United Kingdom strong -5.2% − Chimbote, Peru strong -22.8% − Adana, Turkey confused -23.4% − San Pablo, Philippines strong -18.3% − Braila, Romania strong -17.5% − Chiba, Japan strong -24.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Kawachinagano, Japan happy -22.9% − LISBON, Portugal strong -7.5% − Anand, India strong -3.1% − Kitchener, Canada strong -15.2% − South Cambridgeshire, United Kingdom strong -17.7% − Durango, Mexico strong -25.0% − Aguascalientes, Mexico strong -17.6% − Richmond, United States confused -21.8% − Halifax, Canada strong -19.1% − Kisumu, Kenya confused -19.7% − Bareilly, India confused -23.5% − Quezon City, Philippines strong -4.0% − San Jose, United States confused -24.0% − Geelong, Australia confused -2.1% − Kotte, Sri Lanka confused -1.5% − Iseyin, Nigeria happy -22.8% − Nhatrang, Vietnam happy -22.9% − Bridgeport, United States strong -18.9% − Rouen, France strong -6.3% − Jinan, China strong -8.9% − Muntinlupa, Philippines strong -19.8% − Valencia, Venezuela confused -8.0% − Peshawar, Pakistan strong -24.4% −
=
Pórto Velho, Brazil happy − Shuangyashan, China happy − Lipetsk, Russia strong − Nandyal, India happy − Kadhimain, Iraq happy − Juazeiro do Norte, Brazil happy − Sialkote, Pakistan happy − Huaiyin, China happy − Kanhangad, India happy − San Fernando de Apure, Venezuela strong − Moji-Guaçu, Brazil happy − Jinin, China happy − Basingstoke & Deane, United Kingdom happy − Korla, China strong − Guangshui, China happy − Bihar Sharif, India happy − Shaown, China happy − Niiza, Japan happy − Deir El-Zor, Syrian Arab Republic happy − Meizhou, China strong − Taian, China confused − Xiaocan, China happy − Alagoinhas, Brazil strong − Yuncheng, China weak − Evpatoriya, Ukraine happy − Guikong, China happy − Dlepmealow, South Africa happy − Debrezit, Ethiopia happy − Rubtsovsk, Russia happy − Kiselevsk, Russia happy − Kashihara, Japan happy − Novocherkassk, Russia happy − Soyapango, El Salvador happy − Shanwei, China confused − Durg, India weak − Chongli, China weak − Mudangiang, China happy − Khouribga, Morocco sad − Angren, Uzbekistan confused − Taldikorgan, Kazakstan happy − Calithèa, Greece happy − Salamanca, Mexico strong − Dayuan, China happy − Pinxiang, China happy − Colimas, Mexico happy − Sao Joao de Meriti, Brazil happy − Syktivkar, Russia happy − Reggio di Calabria, Italy happy − Xuchang, China happy − Chinhae, Korea, South happy − Kurume, Japan guilty − Jastrzebie - Zdrój, Poland confused − Sirjan, Iran happy − Al-Rakka, Syrian Arab Republic happy − Changweon, Korea, South happy − Ferraz de Vasconcelos, Brazil happy − Artux, China happy − Holon, Israel confused − Nasariya, Iraq happy − Taiyan, China happy − Sidi-bel-Abbès, Algeria happy − Sao José do Rio Prêto, 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