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
Jequié, Brazil strong +5.6% − San Cristóbal, Venezuela weak +18.5% − Eastleigh, United Kingdom happy +19.0% − Malabon, Philippines happy +23.0% − Nizhnekamsk, Russia confused +21.0% − Oberhausen, Germany weak +19.1% − Ubon Ratchathani, Thailand confused +23.5% − Xichang, China confused +20.3% − La Spezia, Italy confused +22.0% − Sikar, India confused +24.6% − Zonguldak, Turkey strong +22.9% − Thai Nguyen, Vietnam sad +18.1% − Tegal, Indonesia confused +4.6% − Tarragona, Spain strong +21.8% − Kofu, Japan confused +20.9% − Loudi, China weak +17.8% − Gurgaon, India strong +14.2% − Grodno, Belarus sad +19.8% − Oberhausen, Germany weak +19.1% − Tanga, Tanzania confused +20.3% − Chungju, Korea, South sad +4.6% − Yao, Japan strong +22.0% − Vallejo, United States confused +21.9% − Amiens, France confused +22.5% − Waverley, United Kingdom weak +24.4% − Gaya, India strong +23.6% − Giza, Egypt confused +23.8% − Várzea Grande, Brazil strong +21.5% − Kure, Japan happy +17.9% − Abeokuta, Nigeria happy +19.5% − Xichang, China confused +20.3% − Kharagpur, India strong +17.6% − Yokkaichi, Japan strong +19.6% − Diyarbakir, Turkey strong +22.7% − Mbeya, Tanzania confused +22.8% − Smolensk, Russia happy +17.6% − The Wrekin, United Kingdom happy +23.6% − Cardiff, United Kingdom strong +16.1% − Huntington Beach, United States strong +23.2% − Ichikawa, Japan strong +4.5% − Caruaru, Brazil strong +18.6% − Springfield, United States confused +5.1% − Jamalpur, Bangladesh confused +17.7% − Lisburn, United Kingdom strong +19.9% − Daxian, China sad +23.8% − Shaoyang, China weak +21.8% − Chungju, Korea, South sad +4.6% − Vallejo, United States confused +21.9% − Zonguldak, Turkey strong +22.9% − BASSE-TERRE, Guadeloupe strong +24.8% − Lapu-Lapu, Philippines strong +24.6% − Phoenix, United States strong +11.7% − Mönchengladbach, Germany happy +14.7% − Boksburg, South Africa confused +18.1% − Pegu, Myanmar confused +24.1% − Dunfermline, United Kingdom confused +6.9% − East Hampshire, United Kingdom confused +19.0% − BISHKEK, Kyrgyzstan weak +8.9% − Cangzhou, China confused +17.7% − Piracicaba, Brazil strong +20.7% − North York, Canada strong +20.2% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Ubon Ratchathani, Thailand confused +23.5% − TIRANA, Albania sad +18.7% − Tameside, United Kingdom confused +19.1% − Engels, Russia strong +21.7% − Jhang, Pakistan strong +23.9% − Ndola, Zambia happy +17.9% − Unnao, India weak +18.8% − Monywa, Myanmar confused +22.1% − ST. GEORGES, Grenada strong +19.2% − Beaumont, United States confused +12.1% − Engels, Russia strong +21.7% − Raniganj, India confused +23.2% − Waitakere, New Zealand confused +23.5% − Yavatmal, India guilty +24.6% − Burgos, Spain strong +19.8% − Sedgemoor, United Kingdom strong +19.3% − Medellín, Colombia strong +21.8% − San Sebastián, Spain confused +24.0% − Silay, Philippines happy +19.9% − Erlangen, Germany confused +22.9% − Remscheid, Germany strong +19.6% − Pocos de Caldas, Brazil strong +24.0% − Remscheid, Germany strong +19.6% − Abeokuta, Nigeria happy +19.5% − Tacoma, United States confused +20.3% − Baranovichi, Belarus strong +18.5% − Paraná, Argentina strong +12.3% − Hamilton, Canada confused +21.0% − Erbil, Iraq strong +20.1% − PANAMA, Panama strong +3.1% − Pinar del Río, Cuba confused +18.6% − BRIDGETOWN, Barbados confused +23.8% − Chillán, Chile strong +21.7% − Jhang, Pakistan strong +23.9% − Tangshan, China weak +22.3% − Rangpur, Bangladesh happy +24.3% − Pohang, Korea, South confused +21.8% − Ulsan, Korea, South confused +24.5% − Guilin, China strong +3.0% −
Halifax, Canada strong -19.1% − Cochabamba, Bolivia strong -23.2% − Manchester, United Kingdom strong -9.2% − NOUMEA, New Caledonia strong -18.8% − Kotte, Sri Lanka confused -1.5% − Mojokerto, Indonesia strong -13.8% − MONROVIA, Liberia happy -23.4% − Richmond, United States confused -21.8% − Valencia, Venezuela confused -8.0% − Birmingham, United States confused -22.6% − Zaria, Nigeria confused -18.6% − Braila, Romania strong -17.5% − Sapucaia, Brazil strong -18.8% − LISBON, Portugal strong -7.5% − Bareilly, India confused -23.5% − Rouen, France strong -6.3% − Yingcheng, China happy -22.9% − Palakkad, India strong -17.6% − San Pablo, Philippines strong -18.3% − Floridablanca, Colombia strong -22.9% − Irving, United States strong -20.4% − Richmond, United States confused -21.8% − Adana, Turkey confused -23.4% − Leipzig, Germany strong -21.8% − Kochi, India strong -24.8% − South Cambridgeshire, United Kingdom strong -17.7% − Anand, India strong -3.1% − Geelong, Australia confused -2.1% − Magdeburg, Germany strong -23.7% − Quezon City, Philippines strong -4.0% − Tanjung Balai, Indonesia weak -4.9% − Muntinlupa, Philippines strong -19.8% − Brescia, Italy strong -18.6% − Gent, Belgium strong -4.2% − Alexandria, United States strong -11.9% − Sukabumi, Indonesia happy -9.2% − Chicago, United States strong -18.5% − Hampton, United States strong -12.1% − Serra, Brazil strong -5.4% − Bridgeport, United States strong -18.9% − Jersey City, United States strong -23.2% − Jinan, China strong -8.9% − Darlington, United Kingdom strong -24.3% − Teignbridge, United Kingdom confused -20.2% − Peshawar, Pakistan strong -24.4% − Queimados, Brazil strong -20.4% − Jiamusi, China strong -18.6% − Iseyin, Nigeria happy -22.8% − Chiba, Japan strong -24.8% − Ingolstadt, Germany strong -14.9% − Curitiba, Brazil strong -24.8% − Tampa, United States confused -19.1% − Petrópolis, Brazil strong -18.6% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Sefton, United Kingdom strong -5.2% − Gujrat, Pakistan strong -22.0% − Aguascalientes, Mexico strong -17.6% − Dourados, Brazil strong -1.2% − Fukuyama, Japan strong -22.7% − Luohe, China happy -22.9% − Durango, Mexico strong -25.0% − Batangas, Philippines strong -22.8% − Kitchener, Canada strong -15.2% − Amagasaki, Japan happy -24.2% − San Jose, United States confused -24.0% − Kawachinagano, Japan happy -22.9% − Chimbote, Peru strong -22.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Toluca, Mexico confused -22.6% − Nhatrang, Vietnam happy -22.9% − Kisumu, Kenya confused -19.7% − Sergiev Posad, Russia happy -17.8% −
=
Nandyal, India happy − Jinin, China happy − Xuchang, China happy − Niiza, Japan happy − Chinhae, Korea, South happy − Shaown, China happy − Alagoinhas, Brazil strong − Bihar Sharif, India happy − Lipetsk, Russia strong − Pórto Velho, Brazil happy − Mudangiang, China happy − Artux, China happy − Moji-Guaçu, Brazil happy − Salamanca, Mexico strong − Reggio di Calabria, Italy happy − Pinxiang, China happy − Nasariya, Iraq happy − Holon, Israel confused − Sialkote, Pakistan happy − Al-Rakka, Syrian Arab Republic happy − Juazeiro do Norte, Brazil happy − Angren, Uzbekistan confused − Colimas, Mexico happy − Kiselevsk, Russia happy − Sidi-bel-Abbès, Algeria happy − Dayuan, China happy − Kanhangad, India happy − Novocherkassk, Russia happy − Khouribga, Morocco sad − Calithèa, Greece happy − Kurume, Japan guilty − Taiyan, China happy − Sao Joao de Meriti, Brazil happy − Guangshui, China happy − Deir El-Zor, Syrian Arab Republic happy − Kadhimain, Iraq happy − Shanwei, China confused − Durg, India weak − Rubtsovsk, Russia happy − Soyapango, El Salvador happy − Evpatoriya, Ukraine happy − Sao José do Rio Prêto, Brazil happy − Jastrzebie - Zdrój, Poland confused − Syktivkar, Russia happy − Yuncheng, China weak − Korla, China strong − Basingstoke & Deane, United Kingdom happy − Changweon, Korea, South happy − Huaiyin, China happy − Taldikorgan, Kazakstan happy − Kashihara, Japan happy − Meizhou, China strong − Ferraz de Vasconcelos, Brazil happy − San Fernando de Apure, Venezuela strong − Debrezit, Ethiopia happy − Xiaocan, China happy − Dlepmealow, South Africa happy − Taian, China confused − Guikong, China happy − Chongli, China weak − Shuangyashan, China happy − Sirjan, Iran 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