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
Beaumont, United States confused +12.1% − Surakarta, Indonesia strong +20.9% − Unnao, India weak +18.8% − East Hampshire, United Kingdom confused +19.0% − Dunfermline, United Kingdom confused +6.9% − Cardiff, United Kingdom strong +16.1% − BRIDGETOWN, Barbados confused +23.8% − Warren, United States strong +22.1% − LA HABANA, Cuba strong +18.2% − The Wrekin, United Kingdom happy +23.6% − Kure, Japan happy +17.9% − Ambala, India happy +21.8% − Oberhausen, Germany weak +19.1% − Chungju, Korea, South sad +4.6% − Guarapuava, Brazil strong +18.9% − Baranovichi, Belarus strong +18.5% − Gaya, India strong +23.6% − Botou, China strong +24.2% − Yavatmal, India guilty +24.6% − Chon Buri, Thailand strong +23.4% − Medellín, Colombia strong +21.8% − Vallejo, United States confused +21.9% − Monywa, Myanmar confused +22.1% − BASSE-TERRE, Guadeloupe strong +24.8% − ST. GEORGES, Grenada strong +19.2% − Ubon Ratchathani, Thailand confused +23.5% − Arad, Romania strong +11.8% − Pinar del Río, Cuba confused +18.6% − Waitakere, New Zealand confused +23.5% − Lapu-Lapu, Philippines strong +24.6% − Várzea Grande, Brazil strong +21.5% − Ulan-Ude, Russia confused +2.6% − Sedgemoor, United Kingdom strong +19.3% − Caruaru, Brazil strong +18.6% − Huntington Beach, United States strong +23.2% − Susano, Brazil strong +1.7% − Yao, Japan strong +22.0% − Phoenix, United States strong +11.7% − Chillán, Chile strong +21.7% − Pegu, Myanmar confused +24.1% − Anjo, Japan strong +2.2% − Daxian, China sad +23.8% − Erlangen, Germany confused +22.9% − Ichikawa, Japan strong +4.5% − Rangpur, Bangladesh happy +24.3% − Cangzhou, China confused +17.7% − BISHKEK, Kyrgyzstan weak +8.9% − Botou, China strong +24.2% − Tameside, United Kingdom confused +19.1% − Regensburg, Germany strong +16.0% − Silay, Philippines happy +19.9% − Jhang, Pakistan strong +23.9% − Engels, Russia strong +21.7% − Yokkaichi, Japan strong +19.6% − Piracicaba, Brazil strong +20.7% − Raniganj, India confused +23.2% − Guilin, China strong +3.0% − San Cristóbal, Venezuela weak +18.5% − Ubon Ratchathani, Thailand confused +23.5% − Grodno, Belarus sad +19.8% − Mbeya, Tanzania confused +22.8% − The Wrekin, United Kingdom happy +23.6% − La Spezia, Italy confused +22.0% − Diyarbakir, Turkey strong +22.7% − Shaoyang, China weak +21.8% − TIRANA, Albania sad +18.7% − Vallejo, United States confused +21.9% − Pocos de Caldas, Brazil strong +24.0% − Xichang, China confused +20.3% − Burgos, Spain strong +19.8% − Gurgaon, India strong +14.2% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Tacoma, United States confused +20.3% − Nizhnekamsk, Russia confused +21.0% − Hachinohe, Japan strong +21.2% − Pohang, Korea, South confused +21.8% − Giza, Egypt confused +23.8% − Tangshan, China weak +22.3% − Pinar del Río, Cuba confused +18.6% − Remscheid, Germany strong +19.6% − Abeokuta, Nigeria happy +19.5% − Oberhausen, Germany weak +19.1% − Hamilton, Canada confused +21.0% − Mulhouse, France happy +21.4% − Tanga, Tanzania confused +20.3% − Zonguldak, Turkey strong +22.9% − Ulsan, Korea, South confused +24.5% − Eastleigh, United Kingdom happy +19.0% − Mönchengladbach, Germany happy +14.7% − Jequié, Brazil strong +5.6% − Maiduguri, Nigeria confused +21.6% − Laval, Canada strong +10.7% − Sikar, India confused +24.6% − Bobo Dioulasso, Burkina Faso angry +20.4% − San Sebastián, Spain confused +24.0% − Waverley, United Kingdom weak +24.4% − Fukuoka, Japan weak +13.4% − Boksburg, South Africa confused +18.1% − Loudi, China weak +17.8% − Engels, Russia strong +21.7% − Ndola, Zambia happy +17.9% −
Sukabumi, Indonesia happy -9.2% − Bridgeport, United States strong -18.9% − South Cambridgeshire, United Kingdom strong -17.7% − Jinan, China strong -8.9% − Queimados, Brazil strong -20.4% − Petrópolis, Brazil strong -18.6% − NOUMEA, New Caledonia strong -18.8% − Leipzig, Germany strong -21.8% − Tampa, United States confused -19.1% − Darlington, United Kingdom strong -24.3% − MONROVIA, Liberia happy -23.4% − Richmond, United States confused -21.8% − Batangas, Philippines strong -22.8% − Hampton, United States strong -12.1% − Braila, Romania strong -17.5% − Jersey City, United States strong -23.2% − Sergiev Posad, Russia happy -17.8% − Kochi, India strong -24.8% − Manchester, United Kingdom strong -9.2% − Irving, United States strong -20.4% − San Pablo, Philippines strong -18.3% − Sapucaia, Brazil strong -18.8% − Mojokerto, Indonesia strong -13.8% − Kisumu, Kenya confused -19.7% − Kawachinagano, Japan happy -22.9% − Chiba, Japan strong -24.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Curitiba, Brazil strong -24.8% − Dourados, Brazil strong -1.2% − Palakkad, India strong -17.6% − Ingolstadt, Germany strong -14.9% − Chicago, United States strong -18.5% − Bareilly, India confused -23.5% − Birmingham, United States confused -22.6% − Gent, Belgium strong -4.2% − Serra, Brazil strong -5.4% − Durango, Mexico strong -25.0% − Sefton, United Kingdom strong -5.2% − Zaria, Nigeria confused -18.6% − Magdeburg, Germany strong -23.7% − Tanjung Balai, Indonesia weak -4.9% − Iseyin, Nigeria happy -22.8% − Quezon City, Philippines strong -4.0% − Peshawar, Pakistan strong -24.4% − Kitchener, Canada strong -15.2% − Adana, Turkey confused -23.4% − Cochabamba, Bolivia strong -23.2% − Amagasaki, Japan happy -24.2% − Fukuyama, Japan strong -22.7% − Floridablanca, Colombia strong -22.9% − Toluca, Mexico confused -22.6% − Gujrat, Pakistan strong -22.0% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Muntinlupa, Philippines strong -19.8% − Halifax, Canada strong -19.1% − Rouen, France strong -6.3% − San Jose, United States confused -24.0% − Brescia, Italy strong -18.6% − Kotte, Sri Lanka confused -1.5% − Alexandria, United States strong -11.9% − Nhatrang, Vietnam happy -22.9% − Valencia, Venezuela confused -8.0% − Richmond, United States confused -21.8% − Chimbote, Peru strong -22.8% − LISBON, Portugal strong -7.5% − Aguascalientes, Mexico strong -17.6% − Teignbridge, United Kingdom confused -20.2% − Jiamusi, China strong -18.6% − Yingcheng, China happy -22.9% − Anand, India strong -3.1% − Luohe, China happy -22.9% − Geelong, Australia confused -2.1% −
=
Korla, China strong − Holon, Israel confused − Chinhae, Korea, South happy − Guangshui, China happy − Evpatoriya, Ukraine happy − Dlepmealow, South Africa happy − Shaown, China happy − Sao Joao de Meriti, Brazil happy − Sialkote, Pakistan happy − Debrezit, Ethiopia happy − Shuangyashan, China happy − Nandyal, India happy − Pórto Velho, Brazil happy − Alagoinhas, Brazil strong − Jastrzebie - Zdrój, Poland confused − Artux, China happy − Dayuan, China happy − Durg, India weak − Kashihara, Japan happy − Taiyan, China happy − Guikong, China happy − Salamanca, Mexico strong − Basingstoke & Deane, United Kingdom happy − Lipetsk, Russia strong − Angren, Uzbekistan confused − Huaiyin, China happy − Deir El-Zor, Syrian Arab Republic happy − Sidi-bel-Abbès, Algeria happy − Sao José do Rio Prêto, Brazil happy − Ferraz de Vasconcelos, Brazil happy − Rubtsovsk, Russia happy − Meizhou, China strong − Colimas, Mexico happy − San Fernando de Apure, Venezuela strong − Xuchang, China happy − Pinxiang, China happy − Taian, China confused − Kanhangad, India happy − Mudangiang, China happy − Xiaocan, China happy − Novocherkassk, Russia happy − Sirjan, Iran happy − Niiza, Japan happy − Al-Rakka, Syrian Arab Republic happy − Syktivkar, Russia happy − Moji-Guaçu, Brazil happy − Soyapango, El Salvador happy − Kiselevsk, Russia happy − Kurume, Japan guilty − Bihar Sharif, India happy − Khouribga, Morocco sad − Shanwei, China confused − Yuncheng, China weak − Reggio di Calabria, Italy happy − Nasariya, Iraq happy − Juazeiro do Norte, Brazil happy − Chongli, China weak − Taldikorgan, Kazakstan happy − Kadhimain, Iraq happy − Jinin, China happy − Calithèa, Greece happy − Changweon, Korea, South 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