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
Gurgaon, India strong +14.2% − Bobo Dioulasso, Burkina Faso angry +20.4% − Zonguldak, Turkey strong +22.9% − Tacoma, United States confused +20.3% − Boksburg, South Africa confused +18.1% − East Hampshire, United Kingdom confused +19.0% − Remscheid, Germany strong +19.6% − Vallejo, United States confused +21.9% − ROAD TOWN, British Virgin Islands confused +22.0% − Regensburg, Germany strong +16.0% − Gaya, India strong +23.6% − Daxian, China sad +23.8% − La Spezia, Italy confused +22.0% − ST. GEORGES, Grenada strong +19.2% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Oberhausen, Germany weak +19.1% − Pinar del Río, Cuba confused +18.6% − BRIDGETOWN, Barbados confused +23.8% − Shaoyang, China weak +21.8% − Fresno, United States strong +21.7% − Mulhouse, France happy +21.4% − Tarragona, Spain strong +21.8% − Lapu-Lapu, Philippines strong +24.6% − Huntington Beach, United States strong +23.2% − Warren, United States strong +22.1% − Maiduguri, Nigeria confused +21.6% − Erlangen, Germany confused +22.9% − Guarapuava, Brazil strong +18.9% − San Sebastián, Spain confused +24.0% − The Wrekin, United Kingdom happy +23.6% − Rangpur, Bangladesh happy +24.3% − Eastleigh, United Kingdom happy +19.0% − Tacoma, United States confused +20.3% − Pegu, Myanmar confused +24.1% − Botou, China strong +24.2% − Engels, Russia strong +21.7% − Chungju, Korea, South sad +4.6% − Phoenix, United States strong +11.7% − Surakarta, Indonesia strong +20.9% − Tangshan, China weak +22.3% − Tegal, Indonesia confused +4.6% − Várzea Grande, Brazil strong +21.5% − Chillán, Chile strong +21.7% − Abeokuta, Nigeria happy +19.5% − Kure, Japan happy +17.9% − Nizhnekamsk, Russia confused +21.0% − LA HABANA, Cuba strong +18.2% − TIRANA, Albania sad +18.7% − PANAMA, Panama strong +3.1% − Dunfermline, United Kingdom confused +6.9% − Waverley, United Kingdom weak +24.4% − Medellín, Colombia strong +21.8% − Waitakere, New Zealand confused +23.5% − Kofu, Japan confused +20.9% − Xichang, China confused +20.3% − Paraná, Argentina strong +12.3% − Monywa, Myanmar confused +22.1% − Hachinohe, Japan strong +21.2% − Botou, China strong +24.2% − Arad, Romania strong +11.8% − Lisburn, United Kingdom strong +19.9% − Burgos, Spain strong +19.8% − Smolensk, Russia happy +17.6% − Yao, Japan strong +22.0% − Tanga, Tanzania confused +20.3% − Ubon Ratchathani, Thailand confused +23.5% − Gurgaon, India strong +14.2% − Piracicaba, Brazil strong +20.7% − Engels, Russia strong +21.7% − Vallejo, United States confused +21.9% − San Cristóbal, Venezuela weak +18.5% − Zonguldak, Turkey strong +22.9% − Pinar del Río, Cuba confused +18.6% − Chungju, Korea, South sad +4.6% − Sedgemoor, United Kingdom strong +19.3% − BISHKEK, Kyrgyzstan weak +8.9% − BASSE-TERRE, Guadeloupe strong +24.8% − Grodno, Belarus sad +19.8% − Loudi, China weak +17.8% − Thai Nguyen, Vietnam sad +18.1% − Remscheid, Germany strong +19.6% − Mönchengladbach, Germany happy +14.7% − Ulsan, Korea, South confused +24.5% − Cangzhou, China confused +17.7% − Amiens, France confused +22.5% − Abeokuta, Nigeria happy +19.5% − Kharagpur, India strong +17.6% − Jhang, Pakistan strong +23.9% − Tameside, United Kingdom confused +19.1% − Pocos de Caldas, Brazil strong +24.0% − Hamilton, Canada confused +21.0% − The Wrekin, United Kingdom happy +23.6% − Ambala, India happy +21.8% − Mbeya, Tanzania confused +22.8% − Chon Buri, Thailand strong +23.4% − Caruaru, Brazil strong +18.6% − Cardiff, United Kingdom strong +16.1% − Springfield, United States confused +5.1% − Silay, Philippines happy +19.9% − Anyang, China confused +1.0% − Baranovichi, Belarus strong +18.5% −
Magdeburg, Germany strong -23.7% − Adana, Turkey confused -23.4% − Toluca, Mexico confused -22.6% − MONROVIA, Liberia happy -23.4% − Tampa, United States confused -19.1% − Jersey City, United States strong -23.2% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Cochabamba, Bolivia strong -23.2% − Crewe & Nantwich, United Kingdom strong -17.6% − Muntinlupa, Philippines strong -19.8% − Queimados, Brazil strong -20.4% − Kochi, India strong -24.8% − Quezon City, Philippines strong -4.0% − Durango, Mexico strong -25.0% − Hampton, United States strong -12.1% − South Cambridgeshire, United Kingdom strong -17.7% − Batangas, Philippines strong -22.8% − NOUMEA, New Caledonia strong -18.8% − Bareilly, India confused -23.5% − Sergiev Posad, Russia happy -17.8% − San Jose, United States confused -24.0% − Sefton, United Kingdom strong -5.2% − Nhatrang, Vietnam happy -22.9% − Kitchener, Canada strong -15.2% − Aguascalientes, Mexico strong -17.6% − Richmond, United States confused -21.8% − Curitiba, Brazil strong -24.8% − Kotte, Sri Lanka confused -1.5% − Ingolstadt, Germany strong -14.9% − Leipzig, Germany strong -21.8% − Chiba, Japan strong -24.8% − Valencia, Venezuela confused -8.0% − Zaria, Nigeria confused -18.6% − Chicago, United States strong -18.5% − Rouen, France strong -6.3% − Sukabumi, Indonesia happy -9.2% − Irving, United States strong -20.4% − Serra, Brazil strong -5.4% − Bridgeport, United States strong -18.9% − Gujrat, Pakistan strong -22.0% − Teignbridge, United Kingdom confused -20.2% − Alexandria, United States strong -11.9% − Amagasaki, Japan happy -24.2% − Braila, Romania strong -17.5% − Anand, India strong -3.1% − Yingcheng, China happy -22.9% − Birmingham, United States confused -22.6% − Mojokerto, Indonesia strong -13.8% − Petrópolis, Brazil strong -18.6% − Dourados, Brazil strong -1.2% − Palakkad, India strong -17.6% − Luohe, China happy -22.9% − Richmond, United States confused -21.8% − LISBON, Portugal strong -7.5% − Halifax, Canada strong -19.1% − Jinan, China strong -8.9% − Darlington, United Kingdom strong -24.3% − Floridablanca, Colombia strong -22.9% − Geelong, Australia confused -2.1% − Sapucaia, Brazil strong -18.8% − Iseyin, Nigeria happy -22.8% − Fukuyama, Japan strong -22.7% − Kawachinagano, Japan happy -22.9% − Tanjung Balai, Indonesia weak -4.9% − Manchester, United Kingdom strong -9.2% − San Pablo, Philippines strong -18.3% − Gent, Belgium strong -4.2% − Jiamusi, China strong -18.6% − Chimbote, Peru strong -22.8% − Peshawar, Pakistan strong -24.4% − Brescia, Italy strong -18.6% − Kisumu, Kenya confused -19.7% −
=
Guikong, China happy − Xuchang, China happy − Evpatoriya, Ukraine happy − Chinhae, Korea, South happy − Sidi-bel-Abbès, Algeria happy − Moji-Guaçu, Brazil happy − Taiyan, China happy − Soyapango, El Salvador happy − Taldikorgan, Kazakstan happy − Kiselevsk, Russia happy − Colimas, Mexico happy − Jastrzebie - Zdrój, Poland confused − Sao Joao de Meriti, Brazil happy − Jinin, China happy − Debrezit, Ethiopia happy − Kadhimain, Iraq happy − Pórto Velho, Brazil happy − Lipetsk, Russia strong − Meizhou, China strong − Ferraz de Vasconcelos, Brazil happy − Artux, China happy − Shaown, China happy − Dlepmealow, South Africa happy − Salamanca, Mexico strong − Dayuan, China happy − Rubtsovsk, Russia happy − Kurume, Japan guilty − Angren, Uzbekistan confused − Al-Rakka, Syrian Arab Republic happy − Guangshui, China happy − Syktivkar, Russia happy − Taian, China confused − Sirjan, Iran happy − Nasariya, Iraq happy − Sao José do Rio Prêto, Brazil happy − Alagoinhas, Brazil strong − San Fernando de Apure, Venezuela strong − Changweon, Korea, South happy − Chongli, China weak − Huaiyin, China happy − Nandyal, India happy − Bihar Sharif, India happy − Sialkote, Pakistan happy − Calithèa, Greece happy − Shuangyashan, China happy − Pinxiang, China happy − Niiza, Japan happy − Shanwei, China confused − Juazeiro do Norte, Brazil happy − Reggio di Calabria, Italy happy − Durg, India weak − Mudangiang, China happy − Kanhangad, India happy − Yuncheng, China weak − Khouribga, Morocco sad − Xiaocan, China happy − Deir El-Zor, Syrian Arab Republic happy − Korla, China strong − Novocherkassk, Russia happy − Holon, Israel confused − Kashihara, Japan happy − Basingstoke & Deane, United Kingdom 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