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
The Wrekin, United Kingdom happy +23.6% − Abeokuta, Nigeria happy +19.5% − Pocos de Caldas, Brazil strong +24.0% − Ubon Ratchathani, Thailand confused +23.5% − Smolensk, Russia happy +17.6% − Jhang, Pakistan strong +23.9% − Guilin, China strong +3.0% − Unnao, India weak +18.8% − Silay, Philippines happy +19.9% − Baranovichi, Belarus strong +18.5% − Oberhausen, Germany weak +19.1% − Xichang, China confused +20.3% − Tacoma, United States confused +20.3% − Caruaru, Brazil strong +18.6% − Guarapuava, Brazil strong +18.9% − Sedgemoor, United Kingdom strong +19.3% − Zonguldak, Turkey strong +22.9% − Anjo, Japan strong +2.2% − East Hampshire, United Kingdom confused +19.0% − Lisburn, United Kingdom strong +19.9% − Hachinohe, Japan strong +21.2% − Erlangen, Germany confused +22.9% − Lapu-Lapu, Philippines strong +24.6% − Tangshan, China weak +22.3% − Botou, China strong +24.2% − Anyang, China confused +1.0% − Kure, Japan happy +17.9% − Ulan-Ude, Russia confused +2.6% − Yavatmal, India guilty +24.6% − Pinar del Río, Cuba confused +18.6% − Ichikawa, Japan strong +4.5% − Eastleigh, United Kingdom happy +19.0% − Xichang, China confused +20.3% − Abeokuta, Nigeria happy +19.5% − Sikar, India confused +24.6% − Huntington Beach, United States strong +23.2% − Rangpur, Bangladesh happy +24.3% − Monywa, Myanmar confused +22.1% − Loudi, China weak +17.8% − Tarragona, Spain strong +21.8% − The Wrekin, United Kingdom happy +23.6% − Gurgaon, India strong +14.2% − Daxian, China sad +23.8% − Tegal, Indonesia confused +4.6% − North York, Canada strong +20.2% − Oberhausen, Germany weak +19.1% − Jhang, Pakistan strong +23.9% − Ulsan, Korea, South confused +24.5% − San Sebastián, Spain confused +24.0% − LA HABANA, Cuba strong +18.2% − Gaya, India strong +23.6% − Cardiff, United Kingdom strong +16.1% − La Spezia, Italy confused +22.0% − Boksburg, South Africa confused +18.1% − Burgos, Spain strong +19.8% − Regensburg, Germany strong +16.0% − Vadakara, India sad +6.6% − Paraná, Argentina strong +12.3% − Zonguldak, Turkey strong +22.9% − Phoenix, United States strong +11.7% − Vallejo, United States confused +21.9% − Beaumont, United States confused +12.1% − Fresno, United States strong +21.7% − Chungju, Korea, South sad +4.6% − Jamalpur, Bangladesh confused +17.7% − Medellín, Colombia strong +21.8% − Kharagpur, India strong +17.6% − Waitakere, New Zealand confused +23.5% − ROAD TOWN, British Virgin Islands confused +22.0% − Ndola, Zambia happy +17.9% − Hamilton, Canada confused +21.0% − BRIDGETOWN, Barbados confused +23.8% − Giza, Egypt confused +23.8% − San Cristóbal, Venezuela weak +18.5% − Remscheid, Germany strong +19.6% − Remscheid, Germany strong +19.6% − Arad, Romania strong +11.8% − TIRANA, Albania sad +18.7% − Waverley, United Kingdom weak +24.4% − Pinar del Río, Cuba confused +18.6% − Yao, Japan strong +22.0% − Susano, Brazil strong +1.7% − Cangzhou, China confused +17.7% − Mbeya, Tanzania confused +22.8% − Vallejo, United States confused +21.9% − PANAMA, Panama strong +3.1% − Raniganj, India confused +23.2% − Grodno, Belarus sad +19.8% − Jequié, Brazil strong +5.6% − Pegu, Myanmar confused +24.1% − Gurgaon, India strong +14.2% − Tameside, United Kingdom confused +19.1% − Pohang, Korea, South confused +21.8% − Fukuoka, Japan weak +13.4% − Dunfermline, United Kingdom confused +6.9% − Surakarta, Indonesia strong +20.9% − Amiens, France confused +22.5% − Botou, China strong +24.2% − Chungju, Korea, South sad +4.6% − Piracicaba, Brazil strong +20.7% − Shaoyang, China weak +21.8% −
Adana, Turkey confused -23.4% − Batangas, Philippines strong -22.8% − Serra, Brazil strong -5.4% − Aguascalientes, Mexico strong -17.6% − Chicago, United States strong -18.5% − Bareilly, India confused -23.5% − Sergiev Posad, Russia happy -17.8% − Luohe, China happy -22.9% − Curitiba, Brazil strong -24.8% − Queimados, Brazil strong -20.4% − Braila, Romania strong -17.5% − Tampa, United States confused -19.1% − Darlington, United Kingdom strong -24.3% − Chiba, Japan strong -24.8% − Kitchener, Canada strong -15.2% − Chimbote, Peru strong -22.8% − Kotte, Sri Lanka confused -1.5% − Durango, Mexico strong -25.0% − Gent, Belgium strong -4.2% − LISBON, Portugal strong -7.5% − Geelong, Australia confused -2.1% − Petrópolis, Brazil strong -18.6% − Fukuyama, Japan strong -22.7% − Palakkad, India strong -17.6% − Valencia, Venezuela confused -8.0% − Hampton, United States strong -12.1% − Kochi, India strong -24.8% − San Jose, United States confused -24.0% − Bridgeport, United States strong -18.9% − Halifax, Canada strong -19.1% − Manchester, United Kingdom strong -9.2% − Jiamusi, China strong -18.6% − Jinan, China strong -8.9% − Ingolstadt, Germany strong -14.9% − Toluca, Mexico confused -22.6% − Kisumu, Kenya confused -19.7% − Richmond, United States confused -21.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Dourados, Brazil strong -1.2% − Cochabamba, Bolivia strong -23.2% − Sukabumi, Indonesia happy -9.2% − Teignbridge, United Kingdom confused -20.2% − Alexandria, United States strong -11.9% − Irving, United States strong -20.4% − Brescia, Italy strong -18.6% − Birmingham, United States confused -22.6% − Sefton, United Kingdom strong -5.2% − Peshawar, Pakistan strong -24.4% − Gujrat, Pakistan strong -22.0% − Nhatrang, Vietnam happy -22.9% − Amagasaki, Japan happy -24.2% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Yingcheng, China happy -22.9% − NOUMEA, New Caledonia strong -18.8% − Anand, India strong -3.1% − Kawachinagano, Japan happy -22.9% − Muntinlupa, Philippines strong -19.8% − Iseyin, Nigeria happy -22.8% − Sapucaia, Brazil strong -18.8% − South Cambridgeshire, United Kingdom strong -17.7% − Quezon City, Philippines strong -4.0% − MONROVIA, Liberia happy -23.4% − Jersey City, United States strong -23.2% − Magdeburg, Germany strong -23.7% − Rouen, France strong -6.3% − Richmond, United States confused -21.8% − San Pablo, Philippines strong -18.3% − Zaria, Nigeria confused -18.6% − Leipzig, Germany strong -21.8% − Mojokerto, Indonesia strong -13.8% − Floridablanca, Colombia strong -22.9% − Tanjung Balai, Indonesia weak -4.9% −
=
Durg, India weak − Kashihara, Japan happy − Alagoinhas, Brazil strong − Juazeiro do Norte, Brazil happy − Sao Joao de Meriti, Brazil happy − Jinin, China happy − Chongli, China weak − Al-Rakka, Syrian Arab Republic happy − Guangshui, China happy − Basingstoke & Deane, United Kingdom happy − Kiselevsk, Russia happy − Shaown, China happy − Sao José do Rio Prêto, Brazil happy − Meizhou, China strong − Kurume, Japan guilty − Novocherkassk, Russia happy − Debrezit, Ethiopia happy − Holon, Israel confused − Salamanca, Mexico strong − Taian, China confused − Rubtsovsk, Russia happy − Lipetsk, Russia strong − Sidi-bel-Abbès, Algeria happy − Pinxiang, China happy − Huaiyin, China happy − Bihar Sharif, India happy − Moji-Guaçu, Brazil happy − Mudangiang, China happy − Nandyal, India happy − Evpatoriya, Ukraine happy − Guikong, China happy − Yuncheng, China weak − Artux, China happy − Khouribga, Morocco sad − Xiaocan, China happy − Ferraz de Vasconcelos, Brazil happy − Chinhae, Korea, South happy − Calithèa, Greece happy − Sirjan, Iran happy − Angren, Uzbekistan confused − Syktivkar, Russia happy − Shuangyashan, China happy − Soyapango, El Salvador happy − Kadhimain, Iraq happy − Korla, China strong − Nasariya, Iraq happy − Reggio di Calabria, Italy happy − Sialkote, Pakistan happy − Changweon, Korea, South happy − Dlepmealow, South Africa happy − Kanhangad, India happy − Deir El-Zor, Syrian Arab Republic happy − Xuchang, China happy − Niiza, Japan happy − Pórto Velho, Brazil happy − Shanwei, China confused − Dayuan, China happy − Colimas, Mexico happy − Taldikorgan, Kazakstan happy − Taiyan, China happy − San Fernando de Apure, Venezuela strong − Jastrzebie - Zdrój, Poland confused
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