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
Jhang, Pakistan strong +23.9% − Botou, China strong +24.2% − Lapu-Lapu, Philippines strong +24.6% − Caruaru, Brazil strong +18.6% − Pegu, Myanmar confused +24.1% − BRIDGETOWN, Barbados confused +23.8% − Lisburn, United Kingdom strong +19.9% − Abeokuta, Nigeria happy +19.5% − ROAD TOWN, British Virgin Islands confused +22.0% − Zonguldak, Turkey strong +22.9% − San Cristóbal, Venezuela weak +18.5% − Cardiff, United Kingdom strong +16.1% − Tacoma, United States confused +20.3% − Anyang, China confused +1.0% − Rangpur, Bangladesh happy +24.3% − Kharagpur, India strong +17.6% − Phoenix, United States strong +11.7% − Hamilton, Canada confused +21.0% − Huntington Beach, United States strong +23.2% − Baranovichi, Belarus strong +18.5% − Gurgaon, India strong +14.2% − Ichikawa, Japan strong +4.5% − Jhang, Pakistan strong +23.9% − Kofu, Japan confused +20.9% − Warren, United States strong +22.1% − Engels, Russia strong +21.7% − ST. GEORGES, Grenada strong +19.2% − Remscheid, Germany strong +19.6% − North York, Canada strong +20.2% − Dunfermline, United Kingdom confused +6.9% − The Wrekin, United Kingdom happy +23.6% − Jequié, Brazil strong +5.6% − Zonguldak, Turkey strong +22.9% − San Sebastián, Spain confused +24.0% − Abeokuta, Nigeria happy +19.5% − Várzea Grande, Brazil strong +21.5% − Daxian, China sad +23.8% − Regensburg, Germany strong +16.0% − Ubon Ratchathani, Thailand confused +23.5% − Giza, Egypt confused +23.8% − Mönchengladbach, Germany happy +14.7% − Thai Nguyen, Vietnam sad +18.1% − Pinar del Río, Cuba confused +18.6% − Yao, Japan strong +22.0% − Springfield, United States confused +5.1% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Tegal, Indonesia confused +4.6% − Tameside, United Kingdom confused +19.1% − Kure, Japan happy +17.9% − Ubon Ratchathani, Thailand confused +23.5% − Erlangen, Germany confused +22.9% − Nizhnekamsk, Russia confused +21.0% − Unnao, India weak +18.8% − Ambala, India happy +21.8% − Guilin, China strong +3.0% − La Spezia, Italy confused +22.0% − Mulhouse, France happy +21.4% − TIRANA, Albania sad +18.7% − Waitakere, New Zealand confused +23.5% − Malabon, Philippines happy +23.0% − Oberhausen, Germany weak +19.1% − Sedgemoor, United Kingdom strong +19.3% − Botou, China strong +24.2% − Fresno, United States strong +21.7% − Amiens, France confused +22.5% − Laval, Canada strong +10.7% − Remscheid, Germany strong +19.6% − Chillán, Chile strong +21.7% − Yavatmal, India guilty +24.6% − Xichang, China confused +20.3% − Vallejo, United States confused +21.9% − Paraná, Argentina strong +12.3% − Tangshan, China weak +22.3% − Waverley, United Kingdom weak +24.4% − Cangzhou, China confused +17.7% − Smolensk, Russia happy +17.6% − Loudi, China weak +17.8% − Yokkaichi, Japan strong +19.6% − Xichang, China confused +20.3% − Fukuoka, Japan weak +13.4% − Monywa, Myanmar confused +22.1% − LA HABANA, Cuba strong +18.2% − Raniganj, India confused +23.2% − BISHKEK, Kyrgyzstan weak +8.9% − Surakarta, Indonesia strong +20.9% − Bobo Dioulasso, Burkina Faso angry +20.4% − Vadakara, India sad +6.6% − Tarragona, Spain strong +21.8% − Boksburg, South Africa confused +18.1% − Guarapuava, Brazil strong +18.9% − Ulan-Ude, Russia confused +2.6% − Vallejo, United States confused +21.9% − Sikar, India confused +24.6% − PANAMA, Panama strong +3.1% − Gaya, India strong +23.6% − Piracicaba, Brazil strong +20.7% − Tyumen, Russia strong +7.1% − Ulsan, Korea, South confused +24.5% − Medellín, Colombia strong +21.8% − Chungju, Korea, South sad +4.6% − Burgos, Spain strong +19.8% −
Jinan, China strong -8.9% − NOUMEA, New Caledonia strong -18.8% − Chicago, United States strong -18.5% − Tampa, United States confused -19.1% − Anand, India strong -3.1% − Leipzig, Germany strong -21.8% − Darlington, United Kingdom strong -24.3% − Chimbote, Peru strong -22.8% − Crewe & Nantwich, United Kingdom strong -17.6% − San Jose, United States confused -24.0% − Muntinlupa, Philippines strong -19.8% − Toluca, Mexico confused -22.6% − Adana, Turkey confused -23.4% − Kitchener, Canada strong -15.2% − Floridablanca, Colombia strong -22.9% − Gent, Belgium strong -4.2% − Richmond, United States confused -21.8% − Sukabumi, Indonesia happy -9.2% − Braila, Romania strong -17.5% − Kisumu, Kenya confused -19.7% − Kochi, India strong -24.8% − Amagasaki, Japan happy -24.2% − Sapucaia, Brazil strong -18.8% − Durango, Mexico strong -25.0% − Manchester, United Kingdom strong -9.2% − Kotte, Sri Lanka confused -1.5% − Yingcheng, China happy -22.9% − Valencia, Venezuela confused -8.0% − Peshawar, Pakistan strong -24.4% − Brescia, Italy strong -18.6% − San Pablo, Philippines strong -18.3% − Gujrat, Pakistan strong -22.0% − Jiamusi, China strong -18.6% − Fukuyama, Japan strong -22.7% − Mojokerto, Indonesia strong -13.8% − Geelong, Australia confused -2.1% − LISBON, Portugal strong -7.5% − Richmond, United States confused -21.8% − Aguascalientes, Mexico strong -17.6% − Nhatrang, Vietnam happy -22.9% − Iseyin, Nigeria happy -22.8% − Alexandria, United States strong -11.9% − Sergiev Posad, Russia happy -17.8% − Cochabamba, Bolivia strong -23.2% − Bridgeport, United States strong -18.9% − Kawachinagano, Japan happy -22.9% − Chiba, Japan strong -24.8% − South Cambridgeshire, United Kingdom strong -17.7% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Rouen, France strong -6.3% − MONROVIA, Liberia happy -23.4% − Irving, United States strong -20.4% − Serra, Brazil strong -5.4% − Ingolstadt, Germany strong -14.9% − Jersey City, United States strong -23.2% − Halifax, Canada strong -19.1% − Luohe, China happy -22.9% − Batangas, Philippines strong -22.8% − Dourados, Brazil strong -1.2% − Hampton, United States strong -12.1% − Petrópolis, Brazil strong -18.6% − Queimados, Brazil strong -20.4% − Tanjung Balai, Indonesia weak -4.9% − Zaria, Nigeria confused -18.6% − Teignbridge, United Kingdom confused -20.2% − Curitiba, Brazil strong -24.8% − Quezon City, Philippines strong -4.0% − Sefton, United Kingdom strong -5.2% − Birmingham, United States confused -22.6% − Palakkad, India strong -17.6% − Bareilly, India confused -23.5% − Magdeburg, Germany strong -23.7% −
=
Holon, Israel confused − Huaiyin, China happy − Pórto Velho, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Korla, China strong − Kiselevsk, Russia happy − Niiza, Japan happy − Lipetsk, Russia strong − Shuangyashan, China happy − Sidi-bel-Abbès, Algeria happy − Shanwei, China confused − Chongli, China weak − Deir El-Zor, Syrian Arab Republic happy − Dlepmealow, South Africa happy − Mudangiang, China happy − Angren, Uzbekistan confused − Durg, India weak − Khouribga, Morocco sad − Taian, China confused − Novocherkassk, Russia happy − Chinhae, Korea, South happy − Taiyan, China happy − Pinxiang, China happy − Colimas, Mexico happy − Xiaocan, China happy − San Fernando de Apure, Venezuela strong − Rubtsovsk, Russia happy − Reggio di Calabria, Italy happy − Kanhangad, India happy − Kurume, Japan guilty − Basingstoke & Deane, United Kingdom happy − Kashihara, Japan happy − Salamanca, Mexico strong − Jinin, China happy − Debrezit, Ethiopia happy − Nasariya, Iraq happy − Guikong, China happy − Jastrzebie - Zdrój, Poland confused − Changweon, Korea, South happy − Sao José do Rio Prêto, Brazil happy − Kadhimain, Iraq happy − Guangshui, China happy − Sirjan, Iran happy − Meizhou, China strong − Syktivkar, Russia happy − Bihar Sharif, India happy − Ferraz de Vasconcelos, Brazil happy − Artux, China happy − Moji-Guaçu, Brazil happy − Calithèa, Greece happy − Xuchang, China happy − Nandyal, India happy − Taldikorgan, Kazakstan happy − Sialkote, Pakistan happy − Juazeiro do Norte, Brazil happy − Yuncheng, China weak − Evpatoriya, Ukraine happy − Dayuan, China happy − Soyapango, El Salvador happy − Alagoinhas, Brazil strong − Shaown, China 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