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
Ulan-Ude, Russia confused +2.6% − Sikar, India confused +24.6% − Vallejo, United States confused +21.9% − Vadakara, India sad +6.6% − Jhang, Pakistan strong +23.9% − Hamilton, Canada confused +21.0% − Gurgaon, India strong +14.2% − Chillán, Chile strong +21.7% − Waitakere, New Zealand confused +23.5% − Springfield, United States confused +5.1% − Silay, Philippines happy +19.9% − La Spezia, Italy confused +22.0% − Várzea Grande, Brazil strong +21.5% − ROAD TOWN, British Virgin Islands confused +22.0% − Lapu-Lapu, Philippines strong +24.6% − Daxian, China sad +23.8% − Mbeya, Tanzania confused +22.8% − Zonguldak, Turkey strong +22.9% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Cardiff, United Kingdom strong +16.1% − Erlangen, Germany confused +22.9% − Tacoma, United States confused +20.3% − Ndola, Zambia happy +17.9% − Botou, China strong +24.2% − Fresno, United States strong +21.7% − Surakarta, Indonesia strong +20.9% − Abeokuta, Nigeria happy +19.5% − Medellín, Colombia strong +21.8% − Tameside, United Kingdom confused +19.1% − Caruaru, Brazil strong +18.6% − Engels, Russia strong +21.7% − Sedgemoor, United Kingdom strong +19.3% − BISHKEK, Kyrgyzstan weak +8.9% − Oberhausen, Germany weak +19.1% − Yavatmal, India guilty +24.6% − Kharagpur, India strong +17.6% − Eastleigh, United Kingdom happy +19.0% − Ubon Ratchathani, Thailand confused +23.5% − Pinar del Río, Cuba confused +18.6% − Pocos de Caldas, Brazil strong +24.0% − Remscheid, Germany strong +19.6% − Ambala, India happy +21.8% − Warren, United States strong +22.1% − Anjo, Japan strong +2.2% − Chungju, Korea, South sad +4.6% − Jequié, Brazil strong +5.6% − Gurgaon, India strong +14.2% − Tegal, Indonesia confused +4.6% − North York, Canada strong +20.2% − Dunfermline, United Kingdom confused +6.9% − Phoenix, United States strong +11.7% − Chungju, Korea, South sad +4.6% − Paraná, Argentina strong +12.3% − The Wrekin, United Kingdom happy +23.6% − Guilin, China strong +3.0% − TIRANA, Albania sad +18.7% − Tanga, Tanzania confused +20.3% − Anyang, China confused +1.0% − East Hampshire, United Kingdom confused +19.0% − Laval, Canada strong +10.7% − Xichang, China confused +20.3% − Chon Buri, Thailand strong +23.4% − Baranovichi, Belarus strong +18.5% − Burgos, Spain strong +19.8% − Abeokuta, Nigeria happy +19.5% − Boksburg, South Africa confused +18.1% − Yokkaichi, Japan strong +19.6% − ST. GEORGES, Grenada strong +19.2% − Guarapuava, Brazil strong +18.9% − Shaoyang, China weak +21.8% − Yao, Japan strong +22.0% − Monywa, Myanmar confused +22.1% − Mönchengladbach, Germany happy +14.7% − Zonguldak, Turkey strong +22.9% − Pinar del Río, Cuba confused +18.6% − Smolensk, Russia happy +17.6% − Regensburg, Germany strong +16.0% − Piracicaba, Brazil strong +20.7% − Ichikawa, Japan strong +4.5% − Oberhausen, Germany weak +19.1% − Bobo Dioulasso, Burkina Faso angry +20.4% − Tyumen, Russia strong +7.1% − Raniganj, India confused +23.2% − Mulhouse, France happy +21.4% − Erbil, Iraq strong +20.1% − Huntington Beach, United States strong +23.2% − Tarragona, Spain strong +21.8% − Arad, Romania strong +11.8% − Thai Nguyen, Vietnam sad +18.1% − Beaumont, United States confused +12.1% − Xichang, China confused +20.3% − Maiduguri, Nigeria confused +21.6% − Vallejo, United States confused +21.9% − San Sebastián, Spain confused +24.0% − Fukuoka, Japan weak +13.4% − Nizhnekamsk, Russia confused +21.0% − Botou, China strong +24.2% − BRIDGETOWN, Barbados confused +23.8% − The Wrekin, United Kingdom happy +23.6% − Remscheid, Germany strong +19.6% − Malabon, Philippines happy +23.0% −
Jiamusi, China strong -18.6% − Kochi, India strong -24.8% − Muntinlupa, Philippines strong -19.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Darlington, United Kingdom strong -24.3% − Anand, India strong -3.1% − Toluca, Mexico confused -22.6% − Adana, Turkey confused -23.4% − Manchester, United Kingdom strong -9.2% − MONROVIA, Liberia happy -23.4% − Palakkad, India strong -17.6% − Valencia, Venezuela confused -8.0% − Zaria, Nigeria confused -18.6% − Chicago, United States strong -18.5% − Sergiev Posad, Russia happy -17.8% − Alexandria, United States strong -11.9% − Cochabamba, Bolivia strong -23.2% − San Pablo, Philippines strong -18.3% − Rouen, France strong -6.3% − Halifax, Canada strong -19.1% − Petrópolis, Brazil strong -18.6% − Chimbote, Peru strong -22.8% − Jersey City, United States strong -23.2% − Teignbridge, United Kingdom confused -20.2% − Gent, Belgium strong -4.2% − Kotte, Sri Lanka confused -1.5% − Mojokerto, Indonesia strong -13.8% − Richmond, United States confused -21.8% − Jinan, China strong -8.9% − South Cambridgeshire, United Kingdom strong -17.7% − NOUMEA, New Caledonia strong -18.8% − Geelong, Australia confused -2.1% − Bareilly, India confused -23.5% − Dourados, Brazil strong -1.2% − Sukabumi, Indonesia happy -9.2% − Chiba, Japan strong -24.8% − Richmond, United States confused -21.8% − Yingcheng, China happy -22.9% − Kisumu, Kenya confused -19.7% − Floridablanca, Colombia strong -22.9% − Bridgeport, United States strong -18.9% − Kawachinagano, Japan happy -22.9% − Birmingham, United States confused -22.6% − Quezon City, Philippines strong -4.0% − San Jose, United States confused -24.0% − Durango, Mexico strong -25.0% − Batangas, Philippines strong -22.8% − Braila, Romania strong -17.5% − Gujrat, Pakistan strong -22.0% − Curitiba, Brazil strong -24.8% − Leipzig, Germany strong -21.8% − LISBON, Portugal strong -7.5% − Tampa, United States confused -19.1% − Magdeburg, Germany strong -23.7% − Fukuyama, Japan strong -22.7% − Iseyin, Nigeria happy -22.8% − Amagasaki, Japan happy -24.2% − Ingolstadt, Germany strong -14.9% − Queimados, Brazil strong -20.4% − Serra, Brazil strong -5.4% − Irving, United States strong -20.4% − Sefton, United Kingdom strong -5.2% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Hampton, United States strong -12.1% − Nhatrang, Vietnam happy -22.9% − Aguascalientes, Mexico strong -17.6% − Luohe, China happy -22.9% − Brescia, Italy strong -18.6% − Sapucaia, Brazil strong -18.8% − Kitchener, Canada strong -15.2% − Peshawar, Pakistan strong -24.4% − Tanjung Balai, Indonesia weak -4.9% −
=
Evpatoriya, Ukraine happy − Durg, India weak − Calithèa, Greece happy − Kadhimain, Iraq happy − Taian, China confused − Chongli, China weak − Bihar Sharif, India happy − Artux, China happy − Huaiyin, China happy − Debrezit, Ethiopia happy − Mudangiang, China happy − Angren, Uzbekistan confused − Basingstoke & Deane, United Kingdom happy − Reggio di Calabria, Italy happy − Sao Joao de Meriti, Brazil happy − Korla, China strong − Kurume, Japan guilty − Nandyal, India happy − Shuangyashan, China happy − Guangshui, China happy − Guikong, China happy − Changweon, Korea, South happy − Colimas, Mexico happy − Alagoinhas, Brazil strong − Meizhou, China strong − Lipetsk, Russia strong − Sialkote, Pakistan happy − Sao José do Rio Prêto, Brazil happy − Dlepmealow, South Africa happy − Novocherkassk, Russia happy − Yuncheng, China weak − San Fernando de Apure, Venezuela strong − Kanhangad, India happy − Juazeiro do Norte, Brazil happy − Deir El-Zor, Syrian Arab Republic happy − Soyapango, El Salvador happy − Moji-Guaçu, Brazil happy − Shaown, China happy − Kiselevsk, Russia happy − Kashihara, Japan happy − Xiaocan, China happy − Jinin, China happy − Syktivkar, Russia happy − Pórto Velho, Brazil happy − Khouribga, Morocco sad − Taldikorgan, Kazakstan happy − Taiyan, China happy − Dayuan, China happy − Al-Rakka, Syrian Arab Republic happy − Ferraz de Vasconcelos, Brazil happy − Jastrzebie - Zdrój, Poland confused − Holon, Israel confused − Sirjan, Iran happy − Shanwei, China confused − Salamanca, Mexico strong − Xuchang, China happy − Rubtsovsk, Russia happy − Chinhae, Korea, South happy − Nasariya, Iraq happy − Sidi-bel-Abbès, Algeria happy − Niiza, Japan happy − Pinxiang, China 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