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
Erbil, Iraq strong +20.1% − Susano, Brazil strong +1.7% − Abeokuta, Nigeria happy +19.5% − Daxian, China sad +23.8% − Vallejo, United States confused +21.9% − Nizhnekamsk, Russia confused +21.0% − Smolensk, Russia happy +17.6% − Xichang, China confused +20.3% − Lapu-Lapu, Philippines strong +24.6% − San Sebastián, Spain confused +24.0% − Cangzhou, China confused +17.7% − Ichikawa, Japan strong +4.5% − North York, Canada strong +20.2% − Medellín, Colombia strong +21.8% − Unnao, India weak +18.8% − Guilin, China strong +3.0% − Jequié, Brazil strong +5.6% − Surakarta, Indonesia strong +20.9% − Ubon Ratchathani, Thailand confused +23.5% − BASSE-TERRE, Guadeloupe strong +24.8% − Oberhausen, Germany weak +19.1% − Remscheid, Germany strong +19.6% − Bobo Dioulasso, Burkina Faso angry +20.4% − Thai Nguyen, Vietnam sad +18.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Diyarbakir, Turkey strong +22.7% − BISHKEK, Kyrgyzstan weak +8.9% − Ulan-Ude, Russia confused +2.6% − Pegu, Myanmar confused +24.1% − Pohang, Korea, South confused +21.8% − Hamilton, Canada confused +21.0% − Piracicaba, Brazil strong +20.7% − Paraná, Argentina strong +12.3% − Engels, Russia strong +21.7% − Ubon Ratchathani, Thailand confused +23.5% − Caruaru, Brazil strong +18.6% − Erlangen, Germany confused +22.9% − Pinar del Río, Cuba confused +18.6% − Amiens, France confused +22.5% − Ulsan, Korea, South confused +24.5% − Tarragona, Spain strong +21.8% − Yokkaichi, Japan strong +19.6% − Waitakere, New Zealand confused +23.5% − Jhang, Pakistan strong +23.9% − Vallejo, United States confused +21.9% − Remscheid, Germany strong +19.6% − Botou, China strong +24.2% − Tacoma, United States confused +20.3% − Warren, United States strong +22.1% − Chon Buri, Thailand strong +23.4% − Tameside, United Kingdom confused +19.1% − LA HABANA, Cuba strong +18.2% − Monywa, Myanmar confused +22.1% − Zonguldak, Turkey strong +22.9% − Chungju, Korea, South sad +4.6% − Silay, Philippines happy +19.9% − Pinar del Río, Cuba confused +18.6% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Giza, Egypt confused +23.8% − Loudi, China weak +17.8% − Sikar, India confused +24.6% − ST. GEORGES, Grenada strong +19.2% − Cardiff, United Kingdom strong +16.1% − BRIDGETOWN, Barbados confused +23.8% − Springfield, United States confused +5.1% − Gurgaon, India strong +14.2% − Kofu, Japan confused +20.9% − Várzea Grande, Brazil strong +21.5% − Yavatmal, India guilty +24.6% − Regensburg, Germany strong +16.0% − Beaumont, United States confused +12.1% − Grodno, Belarus sad +19.8% − Mulhouse, France happy +21.4% − Rangpur, Bangladesh happy +24.3% − Maiduguri, Nigeria confused +21.6% − Ambala, India happy +21.8% − Tanga, Tanzania confused +20.3% − Kharagpur, India strong +17.6% − Gaya, India strong +23.6% − Boksburg, South Africa confused +18.1% − Gurgaon, India strong +14.2% − The Wrekin, United Kingdom happy +23.6% − Guarapuava, Brazil strong +18.9% − Botou, China strong +24.2% − Arad, Romania strong +11.8% − Burgos, Spain strong +19.8% − Dunfermline, United Kingdom confused +6.9% − Mbeya, Tanzania confused +22.8% − Tegal, Indonesia confused +4.6% − Eastleigh, United Kingdom happy +19.0% − Chungju, Korea, South sad +4.6% − Xichang, China confused +20.3% − Ndola, Zambia happy +17.9% − East Hampshire, United Kingdom confused +19.0% − Pocos de Caldas, Brazil strong +24.0% − La Spezia, Italy confused +22.0% − Sedgemoor, United Kingdom strong +19.3% − The Wrekin, United Kingdom happy +23.6% − Laval, Canada strong +10.7% − Jamalpur, Bangladesh confused +17.7% − Chillán, Chile strong +21.7% −
Zaria, Nigeria confused -18.6% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Tanjung Balai, Indonesia weak -4.9% − Toluca, Mexico confused -22.6% − Mojokerto, Indonesia strong -13.8% − Teignbridge, United Kingdom confused -20.2% − Anand, India strong -3.1% − Braila, Romania strong -17.5% − Kotte, Sri Lanka confused -1.5% − Rouen, France strong -6.3% − Fukuyama, Japan strong -22.7% − Palakkad, India strong -17.6% − Batangas, Philippines strong -22.8% − Kochi, India strong -24.8% − Serra, Brazil strong -5.4% − Quezon City, Philippines strong -4.0% − Ingolstadt, Germany strong -14.9% − Sefton, United Kingdom strong -5.2% − Nhatrang, Vietnam happy -22.9% − Alexandria, United States strong -11.9% − Darlington, United Kingdom strong -24.3% − Chicago, United States strong -18.5% − Geelong, Australia confused -2.1% − Brescia, Italy strong -18.6% − Jinan, China strong -8.9% − Iseyin, Nigeria happy -22.8% − Kawachinagano, Japan happy -22.9% − Sukabumi, Indonesia happy -9.2% − Sapucaia, Brazil strong -18.8% − Tampa, United States confused -19.1% − Crewe & Nantwich, United Kingdom strong -17.6% − Chiba, Japan strong -24.8% − Bridgeport, United States strong -18.9% − Gujrat, Pakistan strong -22.0% − Adana, Turkey confused -23.4% − Curitiba, Brazil strong -24.8% − Halifax, Canada strong -19.1% − Leipzig, Germany strong -21.8% − Jersey City, United States strong -23.2% − San Jose, United States confused -24.0% − Chimbote, Peru strong -22.8% − MONROVIA, Liberia happy -23.4% − Magdeburg, Germany strong -23.7% − Kisumu, Kenya confused -19.7% − NOUMEA, New Caledonia strong -18.8% − Hampton, United States strong -12.1% − Irving, United States strong -20.4% − Muntinlupa, Philippines strong -19.8% − Cochabamba, Bolivia strong -23.2% − Yingcheng, China happy -22.9% − Durango, Mexico strong -25.0% − South Cambridgeshire, United Kingdom strong -17.7% − Sergiev Posad, Russia happy -17.8% − Peshawar, Pakistan strong -24.4% − Amagasaki, Japan happy -24.2% − Dourados, Brazil strong -1.2% − Petrópolis, Brazil strong -18.6% − Bareilly, India confused -23.5% − Kitchener, Canada strong -15.2% − Floridablanca, Colombia strong -22.9% − Richmond, United States confused -21.8% − Jiamusi, China strong -18.6% − Birmingham, United States confused -22.6% − Queimados, Brazil strong -20.4% − Manchester, United Kingdom strong -9.2% − Aguascalientes, Mexico strong -17.6% − Valencia, Venezuela confused -8.0% − Luohe, China happy -22.9% − San Pablo, Philippines strong -18.3% − Richmond, United States confused -21.8% − LISBON, Portugal strong -7.5% − Gent, Belgium strong -4.2% −
=
Novocherkassk, Russia happy − Huaiyin, China happy − Chinhae, Korea, South happy − Evpatoriya, Ukraine happy − Jastrzebie - Zdrój, Poland confused − Korla, China strong − Salamanca, Mexico strong − Kashihara, Japan happy − Alagoinhas, Brazil strong − Xiaocan, China happy − Soyapango, El Salvador happy − Bihar Sharif, India happy − Juazeiro do Norte, Brazil happy − Shuangyashan, China happy − Taian, China confused − Ferraz de Vasconcelos, Brazil happy − Changweon, Korea, South happy − Basingstoke & Deane, United Kingdom happy − Mudangiang, China happy − Reggio di Calabria, Italy happy − Guangshui, China happy − Nasariya, Iraq happy − Sao José do Rio Prêto, Brazil happy − Shanwei, China confused − Deir El-Zor, Syrian Arab Republic happy − Artux, China happy − Taldikorgan, Kazakstan happy − San Fernando de Apure, Venezuela strong − Nandyal, India happy − Al-Rakka, Syrian Arab Republic happy − Kurume, Japan guilty − Dayuan, China happy − Syktivkar, Russia happy − Jinin, China happy − Shaown, China happy − Sirjan, Iran happy − Taiyan, China happy − Pórto Velho, Brazil happy − Holon, Israel confused − Chongli, China weak − Colimas, Mexico happy − Kadhimain, Iraq happy − Durg, India weak − Yuncheng, China weak − Pinxiang, China happy − Khouribga, Morocco sad − Moji-Guaçu, Brazil happy − Kanhangad, India happy − Sialkote, Pakistan happy − Angren, Uzbekistan confused − Xuchang, China happy − Niiza, Japan happy − Meizhou, China strong − Lipetsk, Russia strong − Rubtsovsk, Russia happy − Debrezit, Ethiopia happy − Sao Joao de Meriti, Brazil happy − Dlepmealow, South Africa happy − Calithèa, Greece happy − Sidi-bel-Abbès, Algeria happy − Guikong, China happy − Kiselevsk, 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