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
Chungju, Korea, South sad +4.6% − Paraná, Argentina strong +12.3% − Waitakere, New Zealand confused +23.5% − Susano, Brazil strong +1.7% − Tarragona, Spain strong +21.8% − Jequié, Brazil strong +5.6% − Shaoyang, China weak +21.8% − Vadakara, India sad +6.6% − Chungju, Korea, South sad +4.6% − Tyumen, Russia strong +7.1% − Raniganj, India confused +23.2% − Lisburn, United Kingdom strong +19.9% − Xichang, China confused +20.3% − Daxian, China sad +23.8% − Jhang, Pakistan strong +23.9% − Zonguldak, Turkey strong +22.9% − Pohang, Korea, South confused +21.8% − Tegal, Indonesia confused +4.6% − Caruaru, Brazil strong +18.6% − Tameside, United Kingdom confused +19.1% − Mulhouse, France happy +21.4% − Vallejo, United States confused +21.9% − Gaya, India strong +23.6% − BISHKEK, Kyrgyzstan weak +8.9% − Jhang, Pakistan strong +23.9% − Loudi, China weak +17.8% − Phoenix, United States strong +11.7% − Medellín, Colombia strong +21.8% − Chillán, Chile strong +21.7% − Eastleigh, United Kingdom happy +19.0% − Huntington Beach, United States strong +23.2% − Baranovichi, Belarus strong +18.5% − Mbeya, Tanzania confused +22.8% − BASSE-TERRE, Guadeloupe strong +24.8% − Ndola, Zambia happy +17.9% − Kofu, Japan confused +20.9% − La Spezia, Italy confused +22.0% − Piracicaba, Brazil strong +20.7% − Cangzhou, China confused +17.7% − Dunfermline, United Kingdom confused +6.9% − TIRANA, Albania sad +18.7% − Giza, Egypt confused +23.8% − Tangshan, China weak +22.3% − Beaumont, United States confused +12.1% − Oberhausen, Germany weak +19.1% − Waverley, United Kingdom weak +24.4% − Malabon, Philippines happy +23.0% − Anyang, China confused +1.0% − Ulsan, Korea, South confused +24.5% − Pinar del Río, Cuba confused +18.6% − PANAMA, Panama strong +3.1% − Amiens, France confused +22.5% − Smolensk, Russia happy +17.6% − Ubon Ratchathani, Thailand confused +23.5% − Rangpur, Bangladesh happy +24.3% − Ulan-Ude, Russia confused +2.6% − Lapu-Lapu, Philippines strong +24.6% − Yao, Japan strong +22.0% − BRIDGETOWN, Barbados confused +23.8% − Remscheid, Germany strong +19.6% − The Wrekin, United Kingdom happy +23.6% − Kure, Japan happy +17.9% − San Cristóbal, Venezuela weak +18.5% − Hachinohe, Japan strong +21.2% − Guarapuava, Brazil strong +18.9% − Surakarta, Indonesia strong +20.9% − Engels, Russia strong +21.7% − Guilin, China strong +3.0% − Unnao, India weak +18.8% − Botou, China strong +24.2% − Gurgaon, India strong +14.2% − Hamilton, Canada confused +21.0% − Erlangen, Germany confused +22.9% − Jamalpur, Bangladesh confused +17.7% − Fresno, United States strong +21.7% − Mönchengladbach, Germany happy +14.7% − Ubon Ratchathani, Thailand confused +23.5% − ROAD TOWN, British Virgin Islands confused +22.0% − The Wrekin, United Kingdom happy +23.6% − Laval, Canada strong +10.7% − Springfield, United States confused +5.1% − Tacoma, United States confused +20.3% − Bobo Dioulasso, Burkina Faso angry +20.4% − Pocos de Caldas, Brazil strong +24.0% − Boksburg, South Africa confused +18.1% − San Sebastián, Spain confused +24.0% − Regensburg, Germany strong +16.0% − Várzea Grande, Brazil strong +21.5% − Zonguldak, Turkey strong +22.9% − Yavatmal, India guilty +24.6% − Maiduguri, Nigeria confused +21.6% − Arad, Romania strong +11.8% − Pegu, Myanmar confused +24.1% − ST. GEORGES, Grenada strong +19.2% − Cardiff, United Kingdom strong +16.1% − Abeokuta, Nigeria happy +19.5% − Gurgaon, India strong +14.2% − LA HABANA, Cuba strong +18.2% − Sedgemoor, United Kingdom strong +19.3% − Tanga, Tanzania confused +20.3% − Abeokuta, Nigeria happy +19.5% −
Magdeburg, Germany strong -23.7% − Chimbote, Peru strong -22.8% − Richmond, United States confused -21.8% − Jinan, China strong -8.9% − Quezon City, Philippines strong -4.0% − Crewe & Nantwich, United Kingdom strong -17.6% − Sukabumi, Indonesia happy -9.2% − Valencia, Venezuela confused -8.0% − Peshawar, Pakistan strong -24.4% − Sergiev Posad, Russia happy -17.8% − Palakkad, India strong -17.6% − Alexandria, United States strong -11.9% − Aguascalientes, Mexico strong -17.6% − Fukuyama, Japan strong -22.7% − Amagasaki, Japan happy -24.2% − Braila, Romania strong -17.5% − Gent, Belgium strong -4.2% − Tanjung Balai, Indonesia weak -4.9% − Kochi, India strong -24.8% − Jersey City, United States strong -23.2% − Luohe, China happy -22.9% − Muntinlupa, Philippines strong -19.8% − NOUMEA, New Caledonia strong -18.8% − Ingolstadt, Germany strong -14.9% − Jiamusi, China strong -18.6% − Iseyin, Nigeria happy -22.8% − Anand, India strong -3.1% − Darlington, United Kingdom strong -24.3% − Toluca, Mexico confused -22.6% − Kisumu, Kenya confused -19.7% − MONROVIA, Liberia happy -23.4% − Sefton, United Kingdom strong -5.2% − Birmingham, United States confused -22.6% − Kotte, Sri Lanka confused -1.5% − Kitchener, Canada strong -15.2% − Adana, Turkey confused -23.4% − San Pablo, Philippines strong -18.3% − Bareilly, India confused -23.5% − Leipzig, Germany strong -21.8% − Durango, Mexico strong -25.0% − Serra, Brazil strong -5.4% − Irving, United States strong -20.4% − Manchester, United Kingdom strong -9.2% − Halifax, Canada strong -19.1% − Chicago, United States strong -18.5% − Petrópolis, Brazil strong -18.6% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Batangas, Philippines strong -22.8% − Rouen, France strong -6.3% − Hampton, United States strong -12.1% − Geelong, Australia confused -2.1% − Nhatrang, Vietnam happy -22.9% − Bridgeport, United States strong -18.9% − Zaria, Nigeria confused -18.6% − Dourados, Brazil strong -1.2% − Floridablanca, Colombia strong -22.9% − Yingcheng, China happy -22.9% − Tampa, United States confused -19.1% − Mojokerto, Indonesia strong -13.8% − San Jose, United States confused -24.0% − LISBON, Portugal strong -7.5% − South Cambridgeshire, United Kingdom strong -17.7% − Cochabamba, Bolivia strong -23.2% − Queimados, Brazil strong -20.4% − Brescia, Italy strong -18.6% − Teignbridge, United Kingdom confused -20.2% − Richmond, United States confused -21.8% − Curitiba, Brazil strong -24.8% − Chiba, Japan strong -24.8% − Sapucaia, Brazil strong -18.8% − Kawachinagano, Japan happy -22.9% − Gujrat, Pakistan strong -22.0% −
=
Kanhangad, India happy − Chongli, China weak − Guikong, China happy − Sirjan, Iran happy − Artux, China happy − Debrezit, Ethiopia happy − Xuchang, China happy − Chinhae, Korea, South happy − Syktivkar, Russia happy − Xiaocan, China happy − Durg, India weak − Kiselevsk, Russia happy − Bihar Sharif, India happy − Khouribga, Morocco sad − Lipetsk, Russia strong − Ferraz de Vasconcelos, Brazil happy − Mudangiang, China happy − Shaown, China happy − Angren, Uzbekistan confused − Deir El-Zor, Syrian Arab Republic happy − Dlepmealow, South Africa happy − Pinxiang, China happy − Niiza, Japan happy − Calithèa, Greece happy − Rubtsovsk, Russia happy − Nandyal, India happy − Dayuan, China happy − Kurume, Japan guilty − Jinin, China happy − Moji-Guaçu, Brazil happy − Colimas, Mexico happy − Nasariya, Iraq happy − Holon, Israel confused − Sidi-bel-Abbès, Algeria happy − Sialkote, Pakistan happy − Reggio di Calabria, Italy happy − Taldikorgan, Kazakstan happy − Changweon, Korea, South happy − Sao Joao de Meriti, Brazil happy − Korla, China strong − Shanwei, China confused − Huaiyin, China happy − Alagoinhas, Brazil strong − Taiyan, China happy − Juazeiro do Norte, Brazil happy − Guangshui, China happy − Taian, China confused − Meizhou, China strong − Yuncheng, China weak − Shuangyashan, China happy − San Fernando de Apure, Venezuela strong − Jastrzebie - Zdrój, Poland confused − Al-Rakka, Syrian Arab Republic happy − Kadhimain, Iraq happy − Sao José do Rio Prêto, Brazil happy − Evpatoriya, Ukraine happy − Soyapango, El Salvador happy − Salamanca, Mexico strong − Kashihara, Japan happy − Basingstoke & Deane, United Kingdom happy − Novocherkassk, Russia happy − Pórto Velho, 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