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
Várzea Grande, Brazil strong +21.5% − Malabon, Philippines happy +23.0% − La Spezia, Italy confused +22.0% − Botou, China strong +24.2% − Warren, United States strong +22.1% − Tanga, Tanzania confused +20.3% − Xichang, China confused +20.3% − The Wrekin, United Kingdom happy +23.6% − Jhang, Pakistan strong +23.9% − ROAD TOWN, British Virgin Islands confused +22.0% − Cardiff, United Kingdom strong +16.1% − Diyarbakir, Turkey strong +22.7% − BISHKEK, Kyrgyzstan weak +8.9% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Surakarta, Indonesia strong +20.9% − Remscheid, Germany strong +19.6% − Jhang, Pakistan strong +23.9% − Chon Buri, Thailand strong +23.4% − Botou, China strong +24.2% − Nizhnekamsk, Russia confused +21.0% − Waitakere, New Zealand confused +23.5% − Grodno, Belarus sad +19.8% − Raniganj, India confused +23.2% − Springfield, United States confused +5.1% − Guarapuava, Brazil strong +18.9% − Pocos de Caldas, Brazil strong +24.0% − Hamilton, Canada confused +21.0% − Caruaru, Brazil strong +18.6% − Tameside, United Kingdom confused +19.1% − Paraná, Argentina strong +12.3% − Engels, Russia strong +21.7% − San Cristóbal, Venezuela weak +18.5% − San Sebastián, Spain confused +24.0% − Monywa, Myanmar confused +22.1% − Ichikawa, Japan strong +4.5% − Remscheid, Germany strong +19.6% − Jamalpur, Bangladesh confused +17.7% − Kharagpur, India strong +17.6% − Yokkaichi, Japan strong +19.6% − Ulsan, Korea, South confused +24.5% − Sikar, India confused +24.6% − Pohang, Korea, South confused +21.8% − Eastleigh, United Kingdom happy +19.0% − Tacoma, United States confused +20.3% − Kure, Japan happy +17.9% − Ubon Ratchathani, Thailand confused +23.5% − Mulhouse, France happy +21.4% − LA HABANA, Cuba strong +18.2% − PANAMA, Panama strong +3.1% − Chillán, Chile strong +21.7% − North York, Canada strong +20.2% − Zonguldak, Turkey strong +22.9% − Rangpur, Bangladesh happy +24.3% − Yao, Japan strong +22.0% − Mbeya, Tanzania confused +22.8% − Beaumont, United States confused +12.1% − Anyang, China confused +1.0% − Abeokuta, Nigeria happy +19.5% − Baranovichi, Belarus strong +18.5% − Chungju, Korea, South sad +4.6% − Dunfermline, United Kingdom confused +6.9% − Lapu-Lapu, Philippines strong +24.6% − Engels, Russia strong +21.7% − Mönchengladbach, Germany happy +14.7% − Cangzhou, China confused +17.7% − Chungju, Korea, South sad +4.6% − Abeokuta, Nigeria happy +19.5% − Vallejo, United States confused +21.9% − Pinar del Río, Cuba confused +18.6% − BASSE-TERRE, Guadeloupe strong +24.8% − Fresno, United States strong +21.7% − Burgos, Spain strong +19.8% − BRIDGETOWN, Barbados confused +23.8% − Ulan-Ude, Russia confused +2.6% − Medellín, Colombia strong +21.8% − Erlangen, Germany confused +22.9% − Daxian, China sad +23.8% − Bobo Dioulasso, Burkina Faso angry +20.4% − Waverley, United Kingdom weak +24.4% − Oberhausen, Germany weak +19.1% − Guilin, China strong +3.0% − Laval, Canada strong +10.7% − Maiduguri, Nigeria confused +21.6% − Ambala, India happy +21.8% − Vadakara, India sad +6.6% − Oberhausen, Germany weak +19.1% − Erbil, Iraq strong +20.1% − Lisburn, United Kingdom strong +19.9% − Pinar del Río, Cuba confused +18.6% − Hachinohe, Japan strong +21.2% − Pegu, Myanmar confused +24.1% − Vallejo, United States confused +21.9% − Shaoyang, China weak +21.8% − The Wrekin, United Kingdom happy +23.6% − Arad, Romania strong +11.8% − Jequié, Brazil strong +5.6% − Tegal, Indonesia confused +4.6% − Ndola, Zambia happy +17.9% − Gurgaon, India strong +14.2% − ST. GEORGES, Grenada strong +19.2% − Tangshan, China weak +22.3% −
Alexandria, United States strong -11.9% − Darlington, United Kingdom strong -24.3% − Birmingham, United States confused -22.6% − Durango, Mexico strong -25.0% − LISBON, Portugal strong -7.5% − Queimados, Brazil strong -20.4% − Muntinlupa, Philippines strong -19.8% − Rouen, France strong -6.3% − Kotte, Sri Lanka confused -1.5% − Braila, Romania strong -17.5% − Sukabumi, Indonesia happy -9.2% − Petrópolis, Brazil strong -18.6% − South Cambridgeshire, United Kingdom strong -17.7% − Tanjung Balai, Indonesia weak -4.9% − Zaria, Nigeria confused -18.6% − Floridablanca, Colombia strong -22.9% − Sergiev Posad, Russia happy -17.8% − Nhatrang, Vietnam happy -22.9% − Halifax, Canada strong -19.1% − Tampa, United States confused -19.1% − Peshawar, Pakistan strong -24.4% − Aguascalientes, Mexico strong -17.6% − Magdeburg, Germany strong -23.7% − Luohe, China happy -22.9% − Yingcheng, China happy -22.9% − Sapucaia, Brazil strong -18.8% − Valencia, Venezuela confused -8.0% − Kisumu, Kenya confused -19.7% − Batangas, Philippines strong -22.8% − Irving, United States strong -20.4% − Dourados, Brazil strong -1.2% − Ingolstadt, Germany strong -14.9% − Geelong, Australia confused -2.1% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Gent, Belgium strong -4.2% − Toluca, Mexico confused -22.6% − Kawachinagano, Japan happy -22.9% − Chiba, Japan strong -24.8% − NOUMEA, New Caledonia strong -18.8% − Hampton, United States strong -12.1% − Cochabamba, Bolivia strong -23.2% − Brescia, Italy strong -18.6% − Leipzig, Germany strong -21.8% − Sefton, United Kingdom strong -5.2% − Chicago, United States strong -18.5% − Jiamusi, China strong -18.6% − Teignbridge, United Kingdom confused -20.2% − Manchester, United Kingdom strong -9.2% − Anand, India strong -3.1% − Richmond, United States confused -21.8% − Mojokerto, Indonesia strong -13.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Chimbote, Peru strong -22.8% − Kitchener, Canada strong -15.2% − Palakkad, India strong -17.6% − Gujrat, Pakistan strong -22.0% − San Jose, United States confused -24.0% − Fukuyama, Japan strong -22.7% − Kochi, India strong -24.8% − Jinan, China strong -8.9% − Bridgeport, United States strong -18.9% − Serra, Brazil strong -5.4% − Quezon City, Philippines strong -4.0% − Adana, Turkey confused -23.4% − Richmond, United States confused -21.8% − Bareilly, India confused -23.5% − Amagasaki, Japan happy -24.2% − Curitiba, Brazil strong -24.8% − Iseyin, Nigeria happy -22.8% − San Pablo, Philippines strong -18.3% − Jersey City, United States strong -23.2% − MONROVIA, Liberia happy -23.4% −
=
Colimas, Mexico happy − Xuchang, China happy − San Fernando de Apure, Venezuela strong − Niiza, Japan happy − Basingstoke & Deane, United Kingdom happy − Debrezit, Ethiopia happy − Shaown, China happy − Lipetsk, Russia strong − Chinhae, Korea, South happy − Ferraz de Vasconcelos, Brazil happy − Sao Joao de Meriti, Brazil happy − Syktivkar, Russia happy − Kanhangad, India happy − Rubtsovsk, Russia happy − Nandyal, India happy − Guikong, China happy − Kiselevsk, Russia happy − Taian, China confused − Mudangiang, China happy − Jinin, China happy − Kadhimain, Iraq happy − Chongli, China weak − Bihar Sharif, India happy − Holon, Israel confused − Korla, China strong − Shanwei, China confused − Kashihara, Japan happy − Taldikorgan, Kazakstan happy − Salamanca, Mexico strong − Huaiyin, China happy − Pinxiang, China happy − Sialkote, Pakistan happy − Deir El-Zor, Syrian Arab Republic happy − Soyapango, El Salvador happy − Sirjan, Iran happy − Nasariya, Iraq happy − Khouribga, Morocco sad − Xiaocan, China happy − Yuncheng, China weak − Jastrzebie - Zdrój, Poland confused − Alagoinhas, Brazil strong − Reggio di Calabria, Italy happy − Sidi-bel-Abbès, Algeria happy − Durg, India weak − Guangshui, China happy − Dayuan, China happy − Sao José do Rio Prêto, Brazil happy − Novocherkassk, Russia happy − Al-Rakka, Syrian Arab Republic happy − Changweon, Korea, South happy − Calithèa, Greece happy − Dlepmealow, South Africa happy − Angren, Uzbekistan confused − Shuangyashan, China happy − Moji-Guaçu, Brazil happy − Meizhou, China strong − Artux, China happy − Kurume, Japan guilty − Juazeiro do Norte, Brazil happy − Evpatoriya, Ukraine happy − Taiyan, China 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