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
Amiens, France confused +22.5% − Grodno, Belarus sad +19.8% − Várzea Grande, Brazil strong +21.5% − Dunfermline, United Kingdom confused +6.9% − Cangzhou, China confused +17.7% − Tegal, Indonesia confused +4.6% − Rangpur, Bangladesh happy +24.3% − Tacoma, United States confused +20.3% − Sedgemoor, United Kingdom strong +19.3% − Pohang, Korea, South confused +21.8% − Hamilton, Canada confused +21.0% − Gurgaon, India strong +14.2% − Abeokuta, Nigeria happy +19.5% − Tangshan, China weak +22.3% − Loudi, China weak +17.8% − Yao, Japan strong +22.0% − Silay, Philippines happy +19.9% − Hachinohe, Japan strong +21.2% − Zonguldak, Turkey strong +22.9% − Remscheid, Germany strong +19.6% − Xichang, China confused +20.3% − Diyarbakir, Turkey strong +22.7% − Huntington Beach, United States strong +23.2% − Lisburn, United Kingdom strong +19.9% − Burgos, Spain strong +19.8% − Ulan-Ude, Russia confused +2.6% − Tameside, United Kingdom confused +19.1% − Vadakara, India sad +6.6% − BRIDGETOWN, Barbados confused +23.8% − Cardiff, United Kingdom strong +16.1% − LA HABANA, Cuba strong +18.2% − Mönchengladbach, Germany happy +14.7% − Chon Buri, Thailand strong +23.4% − Lapu-Lapu, Philippines strong +24.6% − Chungju, Korea, South sad +4.6% − BASSE-TERRE, Guadeloupe strong +24.8% − Sikar, India confused +24.6% − Laval, Canada strong +10.7% − Arad, Romania strong +11.8% − Botou, China strong +24.2% − Mulhouse, France happy +21.4% − Susano, Brazil strong +1.7% − Oberhausen, Germany weak +19.1% − Piracicaba, Brazil strong +20.7% − Jamalpur, Bangladesh confused +17.7% − Kure, Japan happy +17.9% − Guarapuava, Brazil strong +18.9% − The Wrekin, United Kingdom happy +23.6% − Ndola, Zambia happy +17.9% − Warren, United States strong +22.1% − Regensburg, Germany strong +16.0% − Daxian, China sad +23.8% − Tacoma, United States confused +20.3% − Kofu, Japan confused +20.9% − Gurgaon, India strong +14.2% − Anyang, China confused +1.0% − La Spezia, Italy confused +22.0% − Jequié, Brazil strong +5.6% − Smolensk, Russia happy +17.6% − North York, Canada strong +20.2% − Yokkaichi, Japan strong +19.6% − Nizhnekamsk, Russia confused +21.0% − Mbeya, Tanzania confused +22.8% − Remscheid, Germany strong +19.6% − Guilin, China strong +3.0% − Jhang, Pakistan strong +23.9% − San Cristóbal, Venezuela weak +18.5% − Jhang, Pakistan strong +23.9% − Pinar del Río, Cuba confused +18.6% − Caruaru, Brazil strong +18.6% − Engels, Russia strong +21.7% − Erbil, Iraq strong +20.1% − Paraná, Argentina strong +12.3% − Surakarta, Indonesia strong +20.9% − Vallejo, United States confused +21.9% − Chillán, Chile strong +21.7% − Chungju, Korea, South sad +4.6% − Pinar del Río, Cuba confused +18.6% − Waitakere, New Zealand confused +23.5% − Beaumont, United States confused +12.1% − Unnao, India weak +18.8% − Kharagpur, India strong +17.6% − Oberhausen, Germany weak +19.1% − Ulsan, Korea, South confused +24.5% − Waverley, United Kingdom weak +24.4% − Ubon Ratchathani, Thailand confused +23.5% − Baranovichi, Belarus strong +18.5% − Tarragona, Spain strong +21.8% − Erlangen, Germany confused +22.9% − Fresno, United States strong +21.7% − East Hampshire, United Kingdom confused +19.0% − Ichikawa, Japan strong +4.5% − BISHKEK, Kyrgyzstan weak +8.9% − Medellín, Colombia strong +21.8% − Giza, Egypt confused +23.8% − Raniganj, India confused +23.2% − Fukuoka, Japan weak +13.4% − Gaya, India strong +23.6% − Boksburg, South Africa confused +18.1% − Pegu, Myanmar confused +24.1% − Anjo, Japan strong +2.2% −
Chimbote, Peru strong -22.8% − Jersey City, United States strong -23.2% − MONROVIA, Liberia happy -23.4% − Darlington, United Kingdom strong -24.3% − Kochi, India strong -24.8% − Fukuyama, Japan strong -22.7% − Valencia, Venezuela confused -8.0% − South Cambridgeshire, United Kingdom strong -17.7% − Manchester, United Kingdom strong -9.2% − Gujrat, Pakistan strong -22.0% − Cochabamba, Bolivia strong -23.2% − Bridgeport, United States strong -18.9% − Floridablanca, Colombia strong -22.9% − Ingolstadt, Germany strong -14.9% − Gent, Belgium strong -4.2% − San Jose, United States confused -24.0% − Durango, Mexico strong -25.0% − Nhatrang, Vietnam happy -22.9% − Brescia, Italy strong -18.6% − Alexandria, United States strong -11.9% − LISBON, Portugal strong -7.5% − Yingcheng, China happy -22.9% − Hampton, United States strong -12.1% − Teignbridge, United Kingdom confused -20.2% − Braila, Romania strong -17.5% − Sapucaia, Brazil strong -18.8% − Anand, India strong -3.1% − Zaria, Nigeria confused -18.6% − Petrópolis, Brazil strong -18.6% − Kitchener, Canada strong -15.2% − Queimados, Brazil strong -20.4% − Chicago, United States strong -18.5% − Bareilly, India confused -23.5% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Crewe & Nantwich, United Kingdom strong -17.6% − Chiba, Japan strong -24.8% − Geelong, Australia confused -2.1% − Batangas, Philippines strong -22.8% − Amagasaki, Japan happy -24.2% − Kisumu, Kenya confused -19.7% − Rouen, France strong -6.3% − Muntinlupa, Philippines strong -19.8% − Kotte, Sri Lanka confused -1.5% − Richmond, United States confused -21.8% − Birmingham, United States confused -22.6% − Adana, Turkey confused -23.4% − Magdeburg, Germany strong -23.7% − Jiamusi, China strong -18.6% − Sukabumi, Indonesia happy -9.2% − NOUMEA, New Caledonia strong -18.8% − Luohe, China happy -22.9% − San Pablo, Philippines strong -18.3% − Jinan, China strong -8.9% − Richmond, United States confused -21.8% − Peshawar, Pakistan strong -24.4% − Dourados, Brazil strong -1.2% − Toluca, Mexico confused -22.6% − Serra, Brazil strong -5.4% − Sergiev Posad, Russia happy -17.8% − Sefton, United Kingdom strong -5.2% − Quezon City, Philippines strong -4.0% − Tanjung Balai, Indonesia weak -4.9% − Palakkad, India strong -17.6% − Halifax, Canada strong -19.1% − Irving, United States strong -20.4% − Tampa, United States confused -19.1% − Curitiba, Brazil strong -24.8% − Mojokerto, Indonesia strong -13.8% − Kawachinagano, Japan happy -22.9% − Aguascalientes, Mexico strong -17.6% − Leipzig, Germany strong -21.8% − Iseyin, Nigeria happy -22.8% −
=
Khouribga, Morocco sad − Korla, China strong − Juazeiro do Norte, Brazil happy − Ferraz de Vasconcelos, Brazil happy − Taiyan, China happy − Xiaocan, China happy − Mudangiang, China happy − Durg, India weak − Deir El-Zor, Syrian Arab Republic happy − Huaiyin, China happy − Xuchang, China happy − Angren, Uzbekistan confused − Alagoinhas, Brazil strong − San Fernando de Apure, Venezuela strong − Yuncheng, China weak − Jinin, China happy − Jastrzebie - Zdrój, Poland confused − Shanwei, China confused − Calithèa, Greece happy − Nasariya, Iraq happy − Taldikorgan, Kazakstan happy − Bihar Sharif, India happy − Pórto Velho, Brazil happy − Meizhou, China strong − Kashihara, Japan happy − Niiza, Japan happy − Sirjan, Iran happy − Nandyal, India happy − Debrezit, Ethiopia happy − Reggio di Calabria, Italy happy − Colimas, Mexico happy − Evpatoriya, Ukraine happy − Dlepmealow, South Africa happy − Sialkote, Pakistan happy − Dayuan, China happy − Taian, China confused − Pinxiang, China happy − Chongli, China weak − Shaown, China happy − Kadhimain, Iraq happy − Novocherkassk, Russia happy − Basingstoke & Deane, United Kingdom happy − Artux, China happy − Lipetsk, Russia strong − Guangshui, China happy − Holon, Israel confused − Guikong, China happy − Kanhangad, India happy − Soyapango, El Salvador happy − Sidi-bel-Abbès, Algeria happy − Salamanca, Mexico strong − Changweon, Korea, South happy − Al-Rakka, Syrian Arab Republic happy − Rubtsovsk, Russia happy − Moji-Guaçu, Brazil happy − Sao José do Rio Prêto, Brazil happy − Chinhae, Korea, South happy − Shuangyashan, China happy − Kurume, Japan guilty − Kiselevsk, Russia happy − Syktivkar, Russia happy − Sao Joao de Meriti, 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