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
Shaoyang, China weak +21.8% − Pegu, Myanmar confused +24.1% − Yao, Japan strong +22.0% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − LA HABANA, Cuba strong +18.2% − Baranovichi, Belarus strong +18.5% − Engels, Russia strong +21.7% − Kharagpur, India strong +17.6% − Malabon, Philippines happy +23.0% − Lapu-Lapu, Philippines strong +24.6% − Vadakara, India sad +6.6% − Amiens, France confused +22.5% − Tarragona, Spain strong +21.8% − ST. GEORGES, Grenada strong +19.2% − Guarapuava, Brazil strong +18.9% − Smolensk, Russia happy +17.6% − Loudi, China weak +17.8% − Mulhouse, France happy +21.4% − Xichang, China confused +20.3% − Mönchengladbach, Germany happy +14.7% − Waverley, United Kingdom weak +24.4% − Laval, Canada strong +10.7% − Ambala, India happy +21.8% − The Wrekin, United Kingdom happy +23.6% − Erbil, Iraq strong +20.1% − Tameside, United Kingdom confused +19.1% − Waitakere, New Zealand confused +23.5% − Botou, China strong +24.2% − Yavatmal, India guilty +24.6% − Tyumen, Russia strong +7.1% − Xichang, China confused +20.3% − Sikar, India confused +24.6% − Huntington Beach, United States strong +23.2% − Chon Buri, Thailand strong +23.4% − San Cristóbal, Venezuela weak +18.5% − Ulsan, Korea, South confused +24.5% − BRIDGETOWN, Barbados confused +23.8% − Silay, Philippines happy +19.9% − Dunfermline, United Kingdom confused +6.9% − Ulan-Ude, Russia confused +2.6% − Tacoma, United States confused +20.3% − Fresno, United States strong +21.7% − Tacoma, United States confused +20.3% − Hachinohe, Japan strong +21.2% − Jequié, Brazil strong +5.6% − Nizhnekamsk, Russia confused +21.0% − Zonguldak, Turkey strong +22.9% − Gurgaon, India strong +14.2% − Piracicaba, Brazil strong +20.7% − BASSE-TERRE, Guadeloupe strong +24.8% − Remscheid, Germany strong +19.6% − Cangzhou, China confused +17.7% − Caruaru, Brazil strong +18.6% − ROAD TOWN, British Virgin Islands confused +22.0% − Ubon Ratchathani, Thailand confused +23.5% − Cardiff, United Kingdom strong +16.1% − Botou, China strong +24.2% − Pohang, Korea, South confused +21.8% − Susano, Brazil strong +1.7% − Jamalpur, Bangladesh confused +17.7% − Chungju, Korea, South sad +4.6% − Ndola, Zambia happy +17.9% − Abeokuta, Nigeria happy +19.5% − Boksburg, South Africa confused +18.1% − The Wrekin, United Kingdom happy +23.6% − Mbeya, Tanzania confused +22.8% − Hamilton, Canada confused +21.0% − TIRANA, Albania sad +18.7% − Medellín, Colombia strong +21.8% − Warren, United States strong +22.1% − Thai Nguyen, Vietnam sad +18.1% − Ubon Ratchathani, Thailand confused +23.5% − Springfield, United States confused +5.1% − Sedgemoor, United Kingdom strong +19.3% − Vallejo, United States confused +21.9% − Chungju, Korea, South sad +4.6% − Oberhausen, Germany weak +19.1% − Pinar del Río, Cuba confused +18.6% − Bobo Dioulasso, Burkina Faso angry +20.4% − Chillán, Chile strong +21.7% − Engels, Russia strong +21.7% − Zonguldak, Turkey strong +22.9% − La Spezia, Italy confused +22.0% − Gurgaon, India strong +14.2% − Unnao, India weak +18.8% − Beaumont, United States confused +12.1% − Jhang, Pakistan strong +23.9% − Lisburn, United Kingdom strong +19.9% − Abeokuta, Nigeria happy +19.5% − Oberhausen, Germany weak +19.1% − Anjo, Japan strong +2.2% − BISHKEK, Kyrgyzstan weak +8.9% − Pinar del Río, Cuba confused +18.6% − Burgos, Spain strong +19.8% − Kure, Japan happy +17.9% − Yokkaichi, Japan strong +19.6% − Regensburg, Germany strong +16.0% − Eastleigh, United Kingdom happy +19.0% − Ichikawa, Japan strong +4.5% − North York, Canada strong +20.2% − PANAMA, Panama strong +3.1% −
Fukuyama, Japan strong -22.7% − Geelong, Australia confused -2.1% − Quezon City, Philippines strong -4.0% − Darlington, United Kingdom strong -24.3% − Sukabumi, Indonesia happy -9.2% − Petrópolis, Brazil strong -18.6% − Floridablanca, Colombia strong -22.9% − Chimbote, Peru strong -22.8% − Richmond, United States confused -21.8% − Anand, India strong -3.1% − Curitiba, Brazil strong -24.8% − Gent, Belgium strong -4.2% − San Pablo, Philippines strong -18.3% − Alexandria, United States strong -11.9% − San Jose, United States confused -24.0% − South Cambridgeshire, United Kingdom strong -17.7% − Nhatrang, Vietnam happy -22.9% − Hampton, United States strong -12.1% − Aguascalientes, Mexico strong -17.6% − Queimados, Brazil strong -20.4% − Jersey City, United States strong -23.2% − Halifax, Canada strong -19.1% − Bridgeport, United States strong -18.9% − Birmingham, United States confused -22.6% − Tanjung Balai, Indonesia weak -4.9% − Adana, Turkey confused -23.4% − Peshawar, Pakistan strong -24.4% − NOUMEA, New Caledonia strong -18.8% − Kisumu, Kenya confused -19.7% − Sapucaia, Brazil strong -18.8% − Manchester, United Kingdom strong -9.2% − Iseyin, Nigeria happy -22.8% − Tampa, United States confused -19.1% − Gujrat, Pakistan strong -22.0% − Chicago, United States strong -18.5% − Luohe, China happy -22.9% − Sergiev Posad, Russia happy -17.8% − Chiba, Japan strong -24.8% − Batangas, Philippines strong -22.8% − Brescia, Italy strong -18.6% − Ingolstadt, Germany strong -14.9% − LISBON, Portugal strong -7.5% − Serra, Brazil strong -5.4% − Mojokerto, Indonesia strong -13.8% − Valencia, Venezuela confused -8.0% − Dourados, Brazil strong -1.2% − Rouen, France strong -6.3% − Kochi, India strong -24.8% − Kawachinagano, Japan happy -22.9% − Braila, Romania strong -17.5% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Zaria, Nigeria confused -18.6% − Irving, United States strong -20.4% − Richmond, United States confused -21.8% − Muntinlupa, Philippines strong -19.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Magdeburg, Germany strong -23.7% − Durango, Mexico strong -25.0% − Jiamusi, China strong -18.6% − Kitchener, Canada strong -15.2% − Teignbridge, United Kingdom confused -20.2% − MONROVIA, Liberia happy -23.4% − Jinan, China strong -8.9% − Palakkad, India strong -17.6% − Kotte, Sri Lanka confused -1.5% − Yingcheng, China happy -22.9% − Toluca, Mexico confused -22.6% − Sefton, United Kingdom strong -5.2% − Bareilly, India confused -23.5% − Leipzig, Germany strong -21.8% − Amagasaki, Japan happy -24.2% − Cochabamba, Bolivia strong -23.2% −
=
Juazeiro do Norte, Brazil happy − Sialkote, Pakistan happy − Bihar Sharif, India happy − Khouribga, Morocco sad − Kashihara, Japan happy − Jinin, China happy − Kiselevsk, Russia happy − Nasariya, Iraq happy − Rubtsovsk, Russia happy − Pinxiang, China happy − Changweon, Korea, South happy − Shaown, China happy − Durg, India weak − Xiaocan, China happy − Shanwei, China confused − Niiza, Japan happy − Basingstoke & Deane, United Kingdom happy − Guangshui, China happy − Yuncheng, China weak − Lipetsk, Russia strong − Angren, Uzbekistan confused − Soyapango, El Salvador happy − Sidi-bel-Abbès, Algeria happy − Holon, Israel confused − San Fernando de Apure, Venezuela strong − Taldikorgan, Kazakstan happy − Evpatoriya, Ukraine happy − Salamanca, Mexico strong − Xuchang, China happy − Sirjan, Iran happy − Jastrzebie - Zdrój, Poland confused − Pórto Velho, Brazil happy − Alagoinhas, Brazil strong − Kadhimain, Iraq happy − Dlepmealow, South Africa happy − Reggio di Calabria, Italy happy − Artux, China happy − Deir El-Zor, Syrian Arab Republic happy − Taiyan, China happy − Chongli, China weak − Moji-Guaçu, Brazil happy − Korla, China strong − Huaiyin, China happy − Debrezit, Ethiopia happy − Chinhae, Korea, South happy − Al-Rakka, Syrian Arab Republic happy − Taian, China confused − Sao José do Rio Prêto, Brazil happy − Kurume, Japan guilty − Meizhou, China strong − Sao Joao de Meriti, Brazil happy − Shuangyashan, China happy − Calithèa, Greece happy − Mudangiang, China happy − Kanhangad, India happy − Dayuan, China happy − Nandyal, India happy − Ferraz de Vasconcelos, Brazil happy − Syktivkar, Russia happy − Colimas, Mexico happy − Guikong, China happy − Novocherkassk, Russia 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