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
Waverley, United Kingdom weak +24.4% − Diyarbakir, Turkey strong +22.7% − Loudi, China weak +17.8% − Mulhouse, France happy +21.4% − Ambala, India happy +21.8% − Vadakara, India sad +6.6% − Dunfermline, United Kingdom confused +6.9% − Oberhausen, Germany weak +19.1% − Tarragona, Spain strong +21.8% − Ulsan, Korea, South confused +24.5% − Medellín, Colombia strong +21.8% − Botou, China strong +24.2% − Burgos, Spain strong +19.8% − Vallejo, United States confused +21.9% − Smolensk, Russia happy +17.6% − Chungju, Korea, South sad +4.6% − Pinar del Río, Cuba confused +18.6% − Susano, Brazil strong +1.7% − Baranovichi, Belarus strong +18.5% − Grodno, Belarus sad +19.8% − Giza, Egypt confused +23.8% − Jamalpur, Bangladesh confused +17.7% − Laval, Canada strong +10.7% − Sikar, India confused +24.6% − Kure, Japan happy +17.9% − Beaumont, United States confused +12.1% − Bobo Dioulasso, Burkina Faso angry +20.4% − Arad, Romania strong +11.8% − Gurgaon, India strong +14.2% − Tanga, Tanzania confused +20.3% − Zonguldak, Turkey strong +22.9% − Yao, Japan strong +22.0% − Sedgemoor, United Kingdom strong +19.3% − Engels, Russia strong +21.7% − Lapu-Lapu, Philippines strong +24.6% − Surakarta, Indonesia strong +20.9% − Mönchengladbach, Germany happy +14.7% − Ulan-Ude, Russia confused +2.6% − Boksburg, South Africa confused +18.1% − Anjo, Japan strong +2.2% − Tacoma, United States confused +20.3% − Caruaru, Brazil strong +18.6% − La Spezia, Italy confused +22.0% − LA HABANA, Cuba strong +18.2% − Huntington Beach, United States strong +23.2% − Monywa, Myanmar confused +22.1% − Springfield, United States confused +5.1% − Tyumen, Russia strong +7.1% − Phoenix, United States strong +11.7% − Chillán, Chile strong +21.7% − Ubon Ratchathani, Thailand confused +23.5% − Pinar del Río, Cuba confused +18.6% − Raniganj, India confused +23.2% − San Sebastián, Spain confused +24.0% − San Cristóbal, Venezuela weak +18.5% − Chon Buri, Thailand strong +23.4% − Yokkaichi, Japan strong +19.6% − Cangzhou, China confused +17.7% − Várzea Grande, Brazil strong +21.5% − Paraná, Argentina strong +12.3% − Warren, United States strong +22.1% − Tacoma, United States confused +20.3% − Cardiff, United Kingdom strong +16.1% − Tegal, Indonesia confused +4.6% − Kharagpur, India strong +17.6% − Guilin, China strong +3.0% − BISHKEK, Kyrgyzstan weak +8.9% − Kofu, Japan confused +20.9% − BRIDGETOWN, Barbados confused +23.8% − ROAD TOWN, British Virgin Islands confused +22.0% − Waitakere, New Zealand confused +23.5% − Ichikawa, Japan strong +4.5% − TIRANA, Albania sad +18.7% − Unnao, India weak +18.8% − Nizhnekamsk, Russia confused +21.0% − Daxian, China sad +23.8% − Erbil, Iraq strong +20.1% − Remscheid, Germany strong +19.6% − The Wrekin, United Kingdom happy +23.6% − Lisburn, United Kingdom strong +19.9% − Silay, Philippines happy +19.9% − Fukuoka, Japan weak +13.4% − Botou, China strong +24.2% − Maiduguri, Nigeria confused +21.6% − Engels, Russia strong +21.7% − Fresno, United States strong +21.7% − Jhang, Pakistan strong +23.9% − Hamilton, Canada confused +21.0% − Jequié, Brazil strong +5.6% − ST. GEORGES, Grenada strong +19.2% − Gaya, India strong +23.6% − Xichang, China confused +20.3% − Regensburg, Germany strong +16.0% − Vallejo, United States confused +21.9% − Hachinohe, Japan strong +21.2% − Chungju, Korea, South sad +4.6% − Jhang, Pakistan strong +23.9% − Tangshan, China weak +22.3% − Abeokuta, Nigeria happy +19.5% − Remscheid, Germany strong +19.6% − Shaoyang, China weak +21.8% −
Crewe & Nantwich, United Kingdom strong -17.6% − South Cambridgeshire, United Kingdom strong -17.7% − Magdeburg, Germany strong -23.7% − Kotte, Sri Lanka confused -1.5% − Halifax, Canada strong -19.1% − Sapucaia, Brazil strong -18.8% − Queimados, Brazil strong -20.4% − MONROVIA, Liberia happy -23.4% − Sukabumi, Indonesia happy -9.2% − Adana, Turkey confused -23.4% − Nhatrang, Vietnam happy -22.9% − Mojokerto, Indonesia strong -13.8% − Muntinlupa, Philippines strong -19.8% − Fukuyama, Japan strong -22.7% − Quezon City, Philippines strong -4.0% − Geelong, Australia confused -2.1% − Palakkad, India strong -17.6% − Curitiba, Brazil strong -24.8% − Kitchener, Canada strong -15.2% − Teignbridge, United Kingdom confused -20.2% − Toluca, Mexico confused -22.6% − Braila, Romania strong -17.5% − Floridablanca, Colombia strong -22.9% − Serra, Brazil strong -5.4% − Darlington, United Kingdom strong -24.3% − Rouen, France strong -6.3% − Tanjung Balai, Indonesia weak -4.9% − Sefton, United Kingdom strong -5.2% − Durango, Mexico strong -25.0% − Kawachinagano, Japan happy -22.9% − Tampa, United States confused -19.1% − Peshawar, Pakistan strong -24.4% − Yingcheng, China happy -22.9% − Jiamusi, China strong -18.6% − Aguascalientes, Mexico strong -17.6% − Gent, Belgium strong -4.2% − Anand, India strong -3.1% − Dourados, Brazil strong -1.2% − Bareilly, India confused -23.5% − Chicago, United States strong -18.5% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Leipzig, Germany strong -21.8% − Chiba, Japan strong -24.8% − Petrópolis, Brazil strong -18.6% − Sergiev Posad, Russia happy -17.8% − NOUMEA, New Caledonia strong -18.8% − Jinan, China strong -8.9% − LISBON, Portugal strong -7.5% − Zaria, Nigeria confused -18.6% − Bridgeport, United States strong -18.9% − Chimbote, Peru strong -22.8% − Kochi, India strong -24.8% − Alexandria, United States strong -11.9% − Valencia, Venezuela confused -8.0% − San Jose, United States confused -24.0% − Batangas, Philippines strong -22.8% − Ingolstadt, Germany strong -14.9% − Richmond, United States confused -21.8% − Brescia, Italy strong -18.6% − Irving, United States strong -20.4% − San Pablo, Philippines strong -18.3% − Gujrat, Pakistan strong -22.0% − Manchester, United Kingdom strong -9.2% − Richmond, United States confused -21.8% − Iseyin, Nigeria happy -22.8% − Amagasaki, Japan happy -24.2% − Birmingham, United States confused -22.6% − Cochabamba, Bolivia strong -23.2% − Luohe, China happy -22.9% − Kisumu, Kenya confused -19.7% − Jersey City, United States strong -23.2% − Hampton, United States strong -12.1% −
=
Syktivkar, Russia happy − Mudangiang, China happy − Ferraz de Vasconcelos, Brazil happy − Kashihara, Japan happy − Yuncheng, China weak − Huaiyin, China happy − Sao Joao de Meriti, Brazil happy − Salamanca, Mexico strong − Nandyal, India happy − Chinhae, Korea, South happy − Niiza, Japan happy − Kiselevsk, Russia happy − Soyapango, El Salvador happy − Taldikorgan, Kazakstan happy − Kanhangad, India happy − Xuchang, China happy − Guikong, China happy − Kadhimain, Iraq happy − Colimas, Mexico happy − Korla, China strong − Jastrzebie - Zdrój, Poland confused − Lipetsk, Russia strong − Bihar Sharif, India happy − Xiaocan, China happy − Changweon, Korea, South happy − Sialkote, Pakistan happy − Dayuan, China happy − Kurume, Japan guilty − Pinxiang, China happy − Juazeiro do Norte, Brazil happy − Dlepmealow, South Africa happy − Jinin, China happy − Evpatoriya, Ukraine happy − Pórto Velho, Brazil happy − Shuangyashan, China happy − Sidi-bel-Abbès, Algeria happy − Basingstoke & Deane, United Kingdom happy − Chongli, China weak − Meizhou, China strong − Angren, Uzbekistan confused − Rubtsovsk, Russia happy − Nasariya, Iraq happy − Durg, India weak − Taiyan, China happy − Reggio di Calabria, Italy happy − San Fernando de Apure, Venezuela strong − Calithèa, Greece happy − Novocherkassk, Russia happy − Sao José do Rio Prêto, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Shaown, China happy − Shanwei, China confused − Moji-Guaçu, Brazil happy − Taian, China confused − Deir El-Zor, Syrian Arab Republic happy − Alagoinhas, Brazil strong − Khouribga, Morocco sad − Artux, China happy − Guangshui, China happy − Debrezit, Ethiopia happy − Sirjan, Iran happy − Holon, Israel confused
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