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
Susano, Brazil strong +1.7% − Bobo Dioulasso, Burkina Faso angry +20.4% − Oberhausen, Germany weak +19.1% − Hamilton, Canada confused +21.0% − Piracicaba, Brazil strong +20.7% − Engels, Russia strong +21.7% − Pohang, Korea, South confused +21.8% − Botou, China strong +24.2% − Waitakere, New Zealand confused +23.5% − Yavatmal, India guilty +24.6% − Chon Buri, Thailand strong +23.4% − Kharagpur, India strong +17.6% − Raniganj, India confused +23.2% − Rangpur, Bangladesh happy +24.3% − Surakarta, Indonesia strong +20.9% − Tangshan, China weak +22.3% − Tarragona, Spain strong +21.8% − Silay, Philippines happy +19.9% − Pegu, Myanmar confused +24.1% − Mulhouse, France happy +21.4% − Chungju, Korea, South sad +4.6% − Xichang, China confused +20.3% − Pinar del Río, Cuba confused +18.6% − Engels, Russia strong +21.7% − Loudi, China weak +17.8% − Caruaru, Brazil strong +18.6% − Remscheid, Germany strong +19.6% − Beaumont, United States confused +12.1% − Boksburg, South Africa confused +18.1% − BRIDGETOWN, Barbados confused +23.8% − BISHKEK, Kyrgyzstan weak +8.9% − Guilin, China strong +3.0% − Mbeya, Tanzania confused +22.8% − San Cristóbal, Venezuela weak +18.5% − Vallejo, United States confused +21.9% − Anjo, Japan strong +2.2% − Vallejo, United States confused +21.9% − Nizhnekamsk, Russia confused +21.0% − Tacoma, United States confused +20.3% − Ichikawa, Japan strong +4.5% − Cangzhou, China confused +17.7% − Shaoyang, China weak +21.8% − Ndola, Zambia happy +17.9% − Lapu-Lapu, Philippines strong +24.6% − Tegal, Indonesia confused +4.6% − Huntington Beach, United States strong +23.2% − Tacoma, United States confused +20.3% − LA HABANA, Cuba strong +18.2% − Hachinohe, Japan strong +21.2% − Guarapuava, Brazil strong +18.9% − Arad, Romania strong +11.8% − Warren, United States strong +22.1% − Unnao, India weak +18.8% − Abeokuta, Nigeria happy +19.5% − Sedgemoor, United Kingdom strong +19.3% − Fukuoka, Japan weak +13.4% − TIRANA, Albania sad +18.7% − Jhang, Pakistan strong +23.9% − Waverley, United Kingdom weak +24.4% − Monywa, Myanmar confused +22.1% − Xichang, China confused +20.3% − The Wrekin, United Kingdom happy +23.6% − La Spezia, Italy confused +22.0% − Regensburg, Germany strong +16.0% − North York, Canada strong +20.2% − Paraná, Argentina strong +12.3% − PANAMA, Panama strong +3.1% − Jequié, Brazil strong +5.6% − Zonguldak, Turkey strong +22.9% − Tameside, United Kingdom confused +19.1% − Ubon Ratchathani, Thailand confused +23.5% − The Wrekin, United Kingdom happy +23.6% − Jhang, Pakistan strong +23.9% − Zonguldak, Turkey strong +22.9% − Diyarbakir, Turkey strong +22.7% − Pinar del Río, Cuba confused +18.6% − Amiens, France confused +22.5% − Medellín, Colombia strong +21.8% − Laval, Canada strong +10.7% − Várzea Grande, Brazil strong +21.5% − Phoenix, United States strong +11.7% − Vadakara, India sad +6.6% − Grodno, Belarus sad +19.8% − Chillán, Chile strong +21.7% − Ubon Ratchathani, Thailand confused +23.5% − Sikar, India confused +24.6% − Chungju, Korea, South sad +4.6% − Baranovichi, Belarus strong +18.5% − ST. GEORGES, Grenada strong +19.2% − Ulan-Ude, Russia confused +2.6% − Gaya, India strong +23.6% − Jamalpur, Bangladesh confused +17.7% − Daxian, China sad +23.8% − Ulsan, Korea, South confused +24.5% − Abeokuta, Nigeria happy +19.5% − Cardiff, United Kingdom strong +16.1% − Lisburn, United Kingdom strong +19.9% − Anyang, China confused +1.0% − Erbil, Iraq strong +20.1% − Tanga, Tanzania confused +20.3% − Fresno, United States strong +21.7% −
Tampa, United States confused -19.1% − Sapucaia, Brazil strong -18.8% − Queimados, Brazil strong -20.4% − Jiamusi, China strong -18.6% − Chicago, United States strong -18.5% − Anand, India strong -3.1% − Sefton, United Kingdom strong -5.2% − Alexandria, United States strong -11.9% − Hampton, United States strong -12.1% − Nhatrang, Vietnam happy -22.9% − NOUMEA, New Caledonia strong -18.8% − Dourados, Brazil strong -1.2% − Jersey City, United States strong -23.2% − Bridgeport, United States strong -18.9% − Richmond, United States confused -21.8% − Ingolstadt, Germany strong -14.9% − Kotte, Sri Lanka confused -1.5% − Quezon City, Philippines strong -4.0% − San Pablo, Philippines strong -18.3% − South Cambridgeshire, United Kingdom strong -17.7% − Fukuyama, Japan strong -22.7% − Magdeburg, Germany strong -23.7% − MONROVIA, Liberia happy -23.4% − Halifax, Canada strong -19.1% − Peshawar, Pakistan strong -24.4% − Zaria, Nigeria confused -18.6% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Aguascalientes, Mexico strong -17.6% − Darlington, United Kingdom strong -24.3% − Cochabamba, Bolivia strong -23.2% − Jinan, China strong -8.9% − Gujrat, Pakistan strong -22.0% − Palakkad, India strong -17.6% − Mojokerto, Indonesia strong -13.8% − Brescia, Italy strong -18.6% − Leipzig, Germany strong -21.8% − Valencia, Venezuela confused -8.0% − Sergiev Posad, Russia happy -17.8% − Chimbote, Peru strong -22.8% − Birmingham, United States confused -22.6% − Batangas, Philippines strong -22.8% − Durango, Mexico strong -25.0% − Tanjung Balai, Indonesia weak -4.9% − Adana, Turkey confused -23.4% − Gent, Belgium strong -4.2% − Serra, Brazil strong -5.4% − Teignbridge, United Kingdom confused -20.2% − Braila, Romania strong -17.5% − Kisumu, Kenya confused -19.7% − San Jose, United States confused -24.0% − Toluca, Mexico confused -22.6% − Rouen, France strong -6.3% − Yingcheng, China happy -22.9% − Amagasaki, Japan happy -24.2% − Richmond, United States confused -21.8% − Petrópolis, Brazil strong -18.6% − Crewe & Nantwich, United Kingdom strong -17.6% − Muntinlupa, Philippines strong -19.8% − LISBON, Portugal strong -7.5% − Floridablanca, Colombia strong -22.9% − Kochi, India strong -24.8% − Irving, United States strong -20.4% − Curitiba, Brazil strong -24.8% − Chiba, Japan strong -24.8% − Iseyin, Nigeria happy -22.8% − Manchester, United Kingdom strong -9.2% − Bareilly, India confused -23.5% − Geelong, Australia confused -2.1% − Luohe, China happy -22.9% − Kawachinagano, Japan happy -22.9% − Kitchener, Canada strong -15.2% − Sukabumi, Indonesia happy -9.2% −
=
Chongli, China weak − Bihar Sharif, India happy − Guangshui, China happy − Meizhou, China strong − Khouribga, Morocco sad − Dayuan, China happy − Kiselevsk, Russia happy − Korla, China strong − Pinxiang, China happy − Huaiyin, China happy − Guikong, China happy − Nandyal, India happy − Reggio di Calabria, Italy happy − Shuangyashan, China happy − Moji-Guaçu, Brazil happy − Soyapango, El Salvador happy − Kashihara, Japan happy − Taldikorgan, Kazakstan happy − Jinin, China happy − Kadhimain, Iraq happy − Syktivkar, Russia happy − Taian, China confused − Angren, Uzbekistan confused − Ferraz de Vasconcelos, Brazil happy − Kurume, Japan guilty − Evpatoriya, Ukraine happy − San Fernando de Apure, Venezuela strong − Alagoinhas, Brazil strong − Al-Rakka, Syrian Arab Republic happy − Mudangiang, China happy − Holon, Israel confused − Shanwei, China confused − Taiyan, China happy − Changweon, Korea, South happy − Jastrzebie - Zdrój, Poland confused − Rubtsovsk, Russia happy − Juazeiro do Norte, Brazil happy − Salamanca, Mexico strong − Yuncheng, China weak − Pórto Velho, Brazil happy − Artux, China happy − Xuchang, China happy − Xiaocan, China happy − Dlepmealow, South Africa happy − Sidi-bel-Abbès, Algeria happy − Chinhae, Korea, South happy − Shaown, China happy − Sao José do Rio Prêto, Brazil happy − Calithèa, Greece happy − Sirjan, Iran happy − Lipetsk, Russia strong − Nasariya, Iraq happy − Basingstoke & Deane, United Kingdom happy − Kanhangad, India happy − Novocherkassk, Russia happy − Debrezit, Ethiopia happy − Deir El-Zor, Syrian Arab Republic happy − Colimas, Mexico happy − Durg, India weak − Niiza, Japan happy − Sao Joao de Meriti, Brazil 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