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
Huntington Beach, United States strong +23.2% − Remscheid, Germany strong +19.6% − Silay, Philippines happy +19.9% − Guilin, China strong +3.0% − Shaoyang, China weak +21.8% − Yavatmal, India guilty +24.6% − ST. GEORGES, Grenada strong +19.2% − Sikar, India confused +24.6% − LA HABANA, Cuba strong +18.2% − Ubon Ratchathani, Thailand confused +23.5% − Springfield, United States confused +5.1% − Jequié, Brazil strong +5.6% − Baranovichi, Belarus strong +18.5% − Anjo, Japan strong +2.2% − Regensburg, Germany strong +16.0% − Eastleigh, United Kingdom happy +19.0% − Sedgemoor, United Kingdom strong +19.3% − Grodno, Belarus sad +19.8% − Zonguldak, Turkey strong +22.9% − Chillán, Chile strong +21.7% − Pegu, Myanmar confused +24.1% − ROAD TOWN, British Virgin Islands confused +22.0% − The Wrekin, United Kingdom happy +23.6% − Abeokuta, Nigeria happy +19.5% − Jhang, Pakistan strong +23.9% − Arad, Romania strong +11.8% − The Wrekin, United Kingdom happy +23.6% − Warren, United States strong +22.1% − Mulhouse, France happy +21.4% − Tyumen, Russia strong +7.1% − Mbeya, Tanzania confused +22.8% − Xichang, China confused +20.3% − Smolensk, Russia happy +17.6% − TIRANA, Albania sad +18.7% − Lisburn, United Kingdom strong +19.9% − Chon Buri, Thailand strong +23.4% − Zonguldak, Turkey strong +22.9% − Piracicaba, Brazil strong +20.7% − Rangpur, Bangladesh happy +24.3% − Monywa, Myanmar confused +22.1% − East Hampshire, United Kingdom confused +19.0% − San Cristóbal, Venezuela weak +18.5% − Chungju, Korea, South sad +4.6% − Ichikawa, Japan strong +4.5% − Ubon Ratchathani, Thailand confused +23.5% − Várzea Grande, Brazil strong +21.5% − Guarapuava, Brazil strong +18.9% − Xichang, China confused +20.3% − Ambala, India happy +21.8% − Erlangen, Germany confused +22.9% − Jamalpur, Bangladesh confused +17.7% − Nizhnekamsk, Russia confused +21.0% − Lapu-Lapu, Philippines strong +24.6% − Pohang, Korea, South confused +21.8% − Chungju, Korea, South sad +4.6% − Waitakere, New Zealand confused +23.5% − Boksburg, South Africa confused +18.1% − Kofu, Japan confused +20.9% − Diyarbakir, Turkey strong +22.7% − Surakarta, Indonesia strong +20.9% − Tameside, United Kingdom confused +19.1% − Thai Nguyen, Vietnam sad +18.1% − Malabon, Philippines happy +23.0% − Loudi, China weak +17.8% − North York, Canada strong +20.2% − Jhang, Pakistan strong +23.9% − Fresno, United States strong +21.7% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Engels, Russia strong +21.7% − Laval, Canada strong +10.7% − La Spezia, Italy confused +22.0% − Mönchengladbach, Germany happy +14.7% − San Sebastián, Spain confused +24.0% − BASSE-TERRE, Guadeloupe strong +24.8% − Gurgaon, India strong +14.2% − Hachinohe, Japan strong +21.2% − Medellín, Colombia strong +21.8% − Yao, Japan strong +22.0% − Pinar del Río, Cuba confused +18.6% − Burgos, Spain strong +19.8% − Fukuoka, Japan weak +13.4% − Tangshan, China weak +22.3% − Amiens, France confused +22.5% − Phoenix, United States strong +11.7% − Tacoma, United States confused +20.3% − Cangzhou, China confused +17.7% − Pocos de Caldas, Brazil strong +24.0% − Vallejo, United States confused +21.9% − Hamilton, Canada confused +21.0% − Paraná, Argentina strong +12.3% − Tanga, Tanzania confused +20.3% − Vadakara, India sad +6.6% − BISHKEK, Kyrgyzstan weak +8.9% − Raniganj, India confused +23.2% − Bobo Dioulasso, Burkina Faso angry +20.4% − Botou, China strong +24.2% − Pinar del Río, Cuba confused +18.6% − Cardiff, United Kingdom strong +16.1% − Engels, Russia strong +21.7% − Beaumont, United States confused +12.1% − Oberhausen, Germany weak +19.1% −
Petrópolis, Brazil strong -18.6% − Teignbridge, United Kingdom confused -20.2% − Tanjung Balai, Indonesia weak -4.9% − Sergiev Posad, Russia happy -17.8% − Jiamusi, China strong -18.6% − Durango, Mexico strong -25.0% − Chiba, Japan strong -24.8% − Leipzig, Germany strong -21.8% − Amagasaki, Japan happy -24.2% − Jinan, China strong -8.9% − Kawachinagano, Japan happy -22.9% − Ingolstadt, Germany strong -14.9% − Kisumu, Kenya confused -19.7% − Zaria, Nigeria confused -18.6% − Geelong, Australia confused -2.1% − Chimbote, Peru strong -22.8% − Tampa, United States confused -19.1% − Nhatrang, Vietnam happy -22.9% − Sukabumi, Indonesia happy -9.2% − Adana, Turkey confused -23.4% − Peshawar, Pakistan strong -24.4% − South Cambridgeshire, United Kingdom strong -17.7% − Sefton, United Kingdom strong -5.2% − Valencia, Venezuela confused -8.0% − Birmingham, United States confused -22.6% − Quezon City, Philippines strong -4.0% − Jersey City, United States strong -23.2% − Aguascalientes, Mexico strong -17.6% − Gent, Belgium strong -4.2% − San Jose, United States confused -24.0% − Richmond, United States confused -21.8% − Hampton, United States strong -12.1% − Kochi, India strong -24.8% − Toluca, Mexico confused -22.6% − Serra, Brazil strong -5.4% − Iseyin, Nigeria happy -22.8% − Manchester, United Kingdom strong -9.2% − Kotte, Sri Lanka confused -1.5% − Palakkad, India strong -17.6% − Batangas, Philippines strong -22.8% − Darlington, United Kingdom strong -24.3% − Bareilly, India confused -23.5% − Braila, Romania strong -17.5% − Brescia, Italy strong -18.6% − Kitchener, Canada strong -15.2% − Irving, United States strong -20.4% − Rouen, France strong -6.3% − NOUMEA, New Caledonia strong -18.8% − Sapucaia, Brazil strong -18.8% − San Pablo, Philippines strong -18.3% − Magdeburg, Germany strong -23.7% − Halifax, Canada strong -19.1% − Dourados, Brazil strong -1.2% − Muntinlupa, Philippines strong -19.8% − Mojokerto, Indonesia strong -13.8% − MONROVIA, Liberia happy -23.4% − Fukuyama, Japan strong -22.7% − Yingcheng, China happy -22.9% − Curitiba, Brazil strong -24.8% − Cochabamba, Bolivia strong -23.2% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Gujrat, Pakistan strong -22.0% − Bridgeport, United States strong -18.9% − Chicago, United States strong -18.5% − Anand, India strong -3.1% − Richmond, United States confused -21.8% − Queimados, Brazil strong -20.4% − LISBON, Portugal strong -7.5% − Luohe, China happy -22.9% − Alexandria, United States strong -11.9% − Crewe & Nantwich, United Kingdom strong -17.6% − Floridablanca, Colombia strong -22.9% −
=
Xiaocan, China happy − Kanhangad, India happy − Changweon, Korea, South happy − Colimas, Mexico happy − Lipetsk, Russia strong − Sao Joao de Meriti, Brazil happy − Mudangiang, China happy − Xuchang, China happy − Yuncheng, China weak − Artux, China happy − Korla, China strong − San Fernando de Apure, Venezuela strong − Reggio di Calabria, Italy happy − Ferraz de Vasconcelos, Brazil happy − Debrezit, Ethiopia happy − Calithèa, Greece happy − Moji-Guaçu, Brazil happy − Taiyan, China happy − Rubtsovsk, Russia happy − Jinin, China happy − Novocherkassk, Russia happy − Syktivkar, Russia happy − Kiselevsk, Russia happy − Huaiyin, China happy − Guangshui, China happy − Basingstoke & Deane, United Kingdom happy − Durg, India weak − Dayuan, China happy − Holon, Israel confused − Guikong, China happy − Salamanca, Mexico strong − Pórto Velho, Brazil happy − Alagoinhas, Brazil strong − Angren, Uzbekistan confused − Bihar Sharif, India happy − Evpatoriya, Ukraine happy − Sirjan, Iran happy − Nandyal, India happy − Chongli, China weak − Dlepmealow, South Africa happy − Sialkote, Pakistan happy − Taian, China confused − Shaown, China happy − Meizhou, China strong − Al-Rakka, Syrian Arab Republic happy − Sidi-bel-Abbès, Algeria happy − Chinhae, Korea, South happy − Jastrzebie - Zdrój, Poland confused − Khouribga, Morocco sad − Niiza, Japan happy − Juazeiro do Norte, Brazil happy − Taldikorgan, Kazakstan happy − Nasariya, Iraq happy − Kadhimain, Iraq happy − Deir El-Zor, Syrian Arab Republic happy − Kurume, Japan guilty − Soyapango, El Salvador happy − Shanwei, China confused − Pinxiang, China happy − Shuangyashan, China happy − Kashihara, Japan happy − Sao José do Rio Prêto, 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