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
Tacoma, United States confused +20.3% − Gaya, India strong +23.6% − Mbeya, Tanzania confused +22.8% − Bobo Dioulasso, Burkina Faso angry +20.4% − Beaumont, United States confused +12.1% − ST. GEORGES, Grenada strong +19.2% − PANAMA, Panama strong +3.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Ubon Ratchathani, Thailand confused +23.5% − Waitakere, New Zealand confused +23.5% − Huntington Beach, United States strong +23.2% − BASSE-TERRE, Guadeloupe strong +24.8% − LA HABANA, Cuba strong +18.2% − Anjo, Japan strong +2.2% − Yavatmal, India guilty +24.6% − Springfield, United States confused +5.1% − Tegal, Indonesia confused +4.6% − Phoenix, United States strong +11.7% − Pohang, Korea, South confused +21.8% − Zonguldak, Turkey strong +22.9% − Yao, Japan strong +22.0% − Yokkaichi, Japan strong +19.6% − Vallejo, United States confused +21.9% − Botou, China strong +24.2% − Abeokuta, Nigeria happy +19.5% − Pinar del Río, Cuba confused +18.6% − Lapu-Lapu, Philippines strong +24.6% − Boksburg, South Africa confused +18.1% − Smolensk, Russia happy +17.6% − Pocos de Caldas, Brazil strong +24.0% − Kharagpur, India strong +17.6% − Mulhouse, France happy +21.4% − TIRANA, Albania sad +18.7% − Engels, Russia strong +21.7% − Gurgaon, India strong +14.2% − Dunfermline, United Kingdom confused +6.9% − Guarapuava, Brazil strong +18.9% − Chillán, Chile strong +21.7% − Amiens, France confused +22.5% − Guilin, China strong +3.0% − Várzea Grande, Brazil strong +21.5% − Abeokuta, Nigeria happy +19.5% − Piracicaba, Brazil strong +20.7% − Medellín, Colombia strong +21.8% − Shaoyang, China weak +21.8% − San Sebastián, Spain confused +24.0% − Gurgaon, India strong +14.2% − Arad, Romania strong +11.8% − Jamalpur, Bangladesh confused +17.7% − Eastleigh, United Kingdom happy +19.0% − The Wrekin, United Kingdom happy +23.6% − Daxian, China sad +23.8% − Malabon, Philippines happy +23.0% − Tyumen, Russia strong +7.1% − Regensburg, Germany strong +16.0% − Raniganj, India confused +23.2% − Maiduguri, Nigeria confused +21.6% − Vallejo, United States confused +21.9% − Botou, China strong +24.2% − Diyarbakir, Turkey strong +22.7% − East Hampshire, United Kingdom confused +19.0% − Waverley, United Kingdom weak +24.4% − Tanga, Tanzania confused +20.3% − Vadakara, India sad +6.6% − The Wrekin, United Kingdom happy +23.6% − Sikar, India confused +24.6% − Anyang, China confused +1.0% − Silay, Philippines happy +19.9% − Ulan-Ude, Russia confused +2.6% − Paraná, Argentina strong +12.3% − Tangshan, China weak +22.3% − Chungju, Korea, South sad +4.6% − Erlangen, Germany confused +22.9% − San Cristóbal, Venezuela weak +18.5% − La Spezia, Italy confused +22.0% − Ichikawa, Japan strong +4.5% − Mönchengladbach, Germany happy +14.7% − Tameside, United Kingdom confused +19.1% − Ulsan, Korea, South confused +24.5% − Fresno, United States strong +21.7% − Tacoma, United States confused +20.3% − Fukuoka, Japan weak +13.4% − Pinar del Río, Cuba confused +18.6% − BRIDGETOWN, Barbados confused +23.8% − Warren, United States strong +22.1% − Jhang, Pakistan strong +23.9% − Kofu, Japan confused +20.9% − Jhang, Pakistan strong +23.9% − Rangpur, Bangladesh happy +24.3% − Burgos, Spain strong +19.8% − Pegu, Myanmar confused +24.1% − Monywa, Myanmar confused +22.1% − Xichang, China confused +20.3% − Ambala, India happy +21.8% − BISHKEK, Kyrgyzstan weak +8.9% − Ubon Ratchathani, Thailand confused +23.5% − Chon Buri, Thailand strong +23.4% − Unnao, India weak +18.8% − Sedgemoor, United Kingdom strong +19.3% − Baranovichi, Belarus strong +18.5% − Thai Nguyen, Vietnam sad +18.1% −
Hampton, United States strong -12.1% − Bareilly, India confused -23.5% − Tampa, United States confused -19.1% − Richmond, United States confused -21.8% − Chicago, United States strong -18.5% − Kotte, Sri Lanka confused -1.5% − Crewe & Nantwich, United Kingdom strong -17.6% − Peshawar, Pakistan strong -24.4% − Durango, Mexico strong -25.0% − Manchester, United Kingdom strong -9.2% − Cochabamba, Bolivia strong -23.2% − Quezon City, Philippines strong -4.0% − Serra, Brazil strong -5.4% − Dourados, Brazil strong -1.2% − Palakkad, India strong -17.6% − Jinan, China strong -8.9% − San Pablo, Philippines strong -18.3% − Iseyin, Nigeria happy -22.8% − Kisumu, Kenya confused -19.7% − Fukuyama, Japan strong -22.7% − Kitchener, Canada strong -15.2% − Chimbote, Peru strong -22.8% − Petrópolis, Brazil strong -18.6% − Amagasaki, Japan happy -24.2% − Valencia, Venezuela confused -8.0% − Queimados, Brazil strong -20.4% − Irving, United States strong -20.4% − Toluca, Mexico confused -22.6% − Brescia, Italy strong -18.6% − San Jose, United States confused -24.0% − Floridablanca, Colombia strong -22.9% − Yingcheng, China happy -22.9% − Adana, Turkey confused -23.4% − Tanjung Balai, Indonesia weak -4.9% − Alexandria, United States strong -11.9% − Darlington, United Kingdom strong -24.3% − Muntinlupa, Philippines strong -19.8% − Kochi, India strong -24.8% − Halifax, Canada strong -19.1% − Geelong, Australia confused -2.1% − Richmond, United States confused -21.8% − Nhatrang, Vietnam happy -22.9% − Sergiev Posad, Russia happy -17.8% − Bridgeport, United States strong -18.9% − Sefton, United Kingdom strong -5.2% − Chiba, Japan strong -24.8% − Kawachinagano, Japan happy -22.9% − Birmingham, United States confused -22.6% − NOUMEA, New Caledonia strong -18.8% − Sapucaia, Brazil strong -18.8% − South Cambridgeshire, United Kingdom strong -17.7% − Gent, Belgium strong -4.2% − Aguascalientes, Mexico strong -17.6% − Magdeburg, Germany strong -23.7% − Rouen, France strong -6.3% − Jiamusi, China strong -18.6% − Gujrat, Pakistan strong -22.0% − LISBON, Portugal strong -7.5% − Jersey City, United States strong -23.2% − Curitiba, Brazil strong -24.8% − Mojokerto, Indonesia strong -13.8% − Teignbridge, United Kingdom confused -20.2% − Anand, India strong -3.1% − Braila, Romania strong -17.5% − Leipzig, Germany strong -21.8% − Sukabumi, Indonesia happy -9.2% − MONROVIA, Liberia happy -23.4% − Zaria, Nigeria confused -18.6% − Ingolstadt, Germany strong -14.9% − Batangas, Philippines strong -22.8% − Luohe, China happy -22.9% − Santiago de los Caballeros, Dominican Republic confused -18.9% −
=
Sao José do Rio Prêto, Brazil happy − Alagoinhas, Brazil strong − Debrezit, Ethiopia happy − Khouribga, Morocco sad − Nandyal, India happy − Soyapango, El Salvador happy − Korla, China strong − Dlepmealow, South Africa happy − Guikong, China happy − Meizhou, China strong − Novocherkassk, Russia happy − Calithèa, Greece happy − Taian, China confused − Colimas, Mexico happy − Guangshui, China happy − Salamanca, Mexico strong − San Fernando de Apure, Venezuela strong − Pórto Velho, Brazil happy − Changweon, Korea, South happy − Yuncheng, China weak − Deir El-Zor, Syrian Arab Republic happy − Evpatoriya, Ukraine happy − Rubtsovsk, Russia happy − Sidi-bel-Abbès, Algeria happy − Kurume, Japan guilty − Kashihara, Japan happy − Xuchang, China happy − Artux, China happy − Kadhimain, Iraq happy − Lipetsk, Russia strong − Taiyan, China happy − Shuangyashan, China happy − Durg, India weak − Angren, Uzbekistan confused − Syktivkar, Russia happy − Pinxiang, China happy − Sirjan, Iran happy − Reggio di Calabria, Italy happy − Sao Joao de Meriti, Brazil happy − Bihar Sharif, India happy − Nasariya, Iraq happy − Moji-Guaçu, Brazil happy − Chongli, China weak − Taldikorgan, Kazakstan happy − Dayuan, China happy − Juazeiro do Norte, Brazil happy − Jastrzebie - Zdrój, Poland confused − Shanwei, China confused − Kanhangad, India happy − Basingstoke & Deane, United Kingdom happy − Al-Rakka, Syrian Arab Republic happy − Jinin, China happy − Huaiyin, China happy − Mudangiang, China happy − Shaown, China happy − Kiselevsk, Russia happy − Ferraz de Vasconcelos, Brazil happy − Xiaocan, China happy − Holon, Israel confused − Chinhae, Korea, South happy − Sialkote, Pakistan happy − Niiza, Japan 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