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
Oberhausen, Germany weak +19.1% − Pegu, Myanmar confused +24.1% − Xichang, China confused +20.3% − Guilin, China strong +3.0% − Hachinohe, Japan strong +21.2% − East Hampshire, United Kingdom confused +19.0% − Arad, Romania strong +11.8% − Mbeya, Tanzania confused +22.8% − BRIDGETOWN, Barbados confused +23.8% − Cardiff, United Kingdom strong +16.1% − Jhang, Pakistan strong +23.9% − Shaoyang, China weak +21.8% − Pocos de Caldas, Brazil strong +24.0% − Thai Nguyen, Vietnam sad +18.1% − ST. GEORGES, Grenada strong +19.2% − Gaya, India strong +23.6% − Loudi, China weak +17.8% − Sikar, India confused +24.6% − Ndola, Zambia happy +17.9% − Erbil, Iraq strong +20.1% − Grodno, Belarus sad +19.8% − Jamalpur, Bangladesh confused +17.7% − Kure, Japan happy +17.9% − La Spezia, Italy confused +22.0% − Smolensk, Russia happy +17.6% − Kharagpur, India strong +17.6% − Tangshan, China weak +22.3% − Lapu-Lapu, Philippines strong +24.6% − Ubon Ratchathani, Thailand confused +23.5% − Beaumont, United States confused +12.1% − Piracicaba, Brazil strong +20.7% − Phoenix, United States strong +11.7% − Botou, China strong +24.2% − Monywa, Myanmar confused +22.1% − The Wrekin, United Kingdom happy +23.6% − San Cristóbal, Venezuela weak +18.5% − Guarapuava, Brazil strong +18.9% − Amiens, France confused +22.5% − Boksburg, South Africa confused +18.1% − Fukuoka, Japan weak +13.4% − Tacoma, United States confused +20.3% − Daxian, China sad +23.8% − Jequié, Brazil strong +5.6% − Ambala, India happy +21.8% − San Sebastián, Spain confused +24.0% − Pohang, Korea, South confused +21.8% − Silay, Philippines happy +19.9% − Unnao, India weak +18.8% − Tyumen, Russia strong +7.1% − BASSE-TERRE, Guadeloupe strong +24.8% − Lisburn, United Kingdom strong +19.9% − Raniganj, India confused +23.2% − Anyang, China confused +1.0% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Maiduguri, Nigeria confused +21.6% − Pinar del Río, Cuba confused +18.6% − Burgos, Spain strong +19.8% − Nizhnekamsk, Russia confused +21.0% − Pinar del Río, Cuba confused +18.6% − Tameside, United Kingdom confused +19.1% − Fresno, United States strong +21.7% − Regensburg, Germany strong +16.0% − Chungju, Korea, South sad +4.6% − Hamilton, Canada confused +21.0% − Zonguldak, Turkey strong +22.9% − Gurgaon, India strong +14.2% − North York, Canada strong +20.2% − Medellín, Colombia strong +21.8% − Waitakere, New Zealand confused +23.5% − Chon Buri, Thailand strong +23.4% − Ulsan, Korea, South confused +24.5% − Ubon Ratchathani, Thailand confused +23.5% − Vallejo, United States confused +21.9% − BISHKEK, Kyrgyzstan weak +8.9% − Engels, Russia strong +21.7% − Dunfermline, United Kingdom confused +6.9% − Yavatmal, India guilty +24.6% − Tanga, Tanzania confused +20.3% − Vallejo, United States confused +21.9% − Anjo, Japan strong +2.2% − Abeokuta, Nigeria happy +19.5% − Cangzhou, China confused +17.7% − Ichikawa, Japan strong +4.5% − Rangpur, Bangladesh happy +24.3% − Huntington Beach, United States strong +23.2% − Tegal, Indonesia confused +4.6% − The Wrekin, United Kingdom happy +23.6% − Remscheid, Germany strong +19.6% − LA HABANA, Cuba strong +18.2% − Susano, Brazil strong +1.7% − Malabon, Philippines happy +23.0% − Surakarta, Indonesia strong +20.9% − Tacoma, United States confused +20.3% − Diyarbakir, Turkey strong +22.7% − Kofu, Japan confused +20.9% − Jhang, Pakistan strong +23.9% − Erlangen, Germany confused +22.9% − Laval, Canada strong +10.7% − Yao, Japan strong +22.0% − Oberhausen, Germany weak +19.1% − Tarragona, Spain strong +21.8% −
Leipzig, Germany strong -21.8% − Irving, United States strong -20.4% − Dourados, Brazil strong -1.2% − Chicago, United States strong -18.5% − Durango, Mexico strong -25.0% − Toluca, Mexico confused -22.6% − Sefton, United Kingdom strong -5.2% − Bareilly, India confused -23.5% − Adana, Turkey confused -23.4% − Nhatrang, Vietnam happy -22.9% − Muntinlupa, Philippines strong -19.8% − Halifax, Canada strong -19.1% − Birmingham, United States confused -22.6% − Quezon City, Philippines strong -4.0% − Richmond, United States confused -21.8% − Cochabamba, Bolivia strong -23.2% − Valencia, Venezuela confused -8.0% − Chiba, Japan strong -24.8% − Sukabumi, Indonesia happy -9.2% − Queimados, Brazil strong -20.4% − Yingcheng, China happy -22.9% − Kotte, Sri Lanka confused -1.5% − Anand, India strong -3.1% − Bridgeport, United States strong -18.9% − South Cambridgeshire, United Kingdom strong -17.7% − Serra, Brazil strong -5.4% − Manchester, United Kingdom strong -9.2% − Kisumu, Kenya confused -19.7% − Fukuyama, Japan strong -22.7% − Petrópolis, Brazil strong -18.6% − Tampa, United States confused -19.1% − Gent, Belgium strong -4.2% − San Pablo, Philippines strong -18.3% − Chimbote, Peru strong -22.8% − Magdeburg, Germany strong -23.7% − Ingolstadt, Germany strong -14.9% − Teignbridge, United Kingdom confused -20.2% − Geelong, Australia confused -2.1% − Jiamusi, China strong -18.6% − Richmond, United States confused -21.8% − Kawachinagano, Japan happy -22.9% − Hampton, United States strong -12.1% − Sapucaia, Brazil strong -18.8% − Peshawar, Pakistan strong -24.4% − Iseyin, Nigeria happy -22.8% − Alexandria, United States strong -11.9% − Tanjung Balai, Indonesia weak -4.9% − Mojokerto, Indonesia strong -13.8% − Gujrat, Pakistan strong -22.0% − Darlington, United Kingdom strong -24.3% − MONROVIA, Liberia happy -23.4% − Brescia, Italy strong -18.6% − Luohe, China happy -22.9% − Zaria, Nigeria confused -18.6% − LISBON, Portugal strong -7.5% − Rouen, France strong -6.3% − NOUMEA, New Caledonia strong -18.8% − Sergiev Posad, Russia happy -17.8% − Braila, Romania strong -17.5% − Crewe & Nantwich, United Kingdom strong -17.6% − Amagasaki, Japan happy -24.2% − Kochi, India strong -24.8% − Palakkad, India strong -17.6% − Jersey City, United States strong -23.2% − San Jose, United States confused -24.0% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Batangas, Philippines strong -22.8% − Aguascalientes, Mexico strong -17.6% − Curitiba, Brazil strong -24.8% − Kitchener, Canada strong -15.2% − Floridablanca, Colombia strong -22.9% − Jinan, China strong -8.9% −
=
Ferraz de Vasconcelos, Brazil happy − Lipetsk, Russia strong − Shaown, China happy − Pórto Velho, Brazil happy − Salamanca, Mexico strong − Calithèa, Greece happy − Kurume, Japan guilty − Chongli, China weak − Yuncheng, China weak − Taldikorgan, Kazakstan happy − Colimas, Mexico happy − Nasariya, Iraq happy − Nandyal, India happy − Meizhou, China strong − Guikong, China happy − Pinxiang, China happy − Dayuan, China happy − Korla, China strong − Changweon, Korea, South happy − Kashihara, Japan happy − Shanwei, China confused − Evpatoriya, Ukraine happy − Deir El-Zor, Syrian Arab Republic happy − Taian, China confused − Sialkote, Pakistan happy − Sirjan, Iran happy − Sao Joao de Meriti, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Angren, Uzbekistan confused − Niiza, Japan happy − Soyapango, El Salvador happy − Jastrzebie - Zdrój, Poland confused − Basingstoke & Deane, United Kingdom happy − Xiaocan, China happy − Kiselevsk, Russia happy − Mudangiang, China happy − Kanhangad, India happy − Moji-Guaçu, Brazil happy − Huaiyin, China happy − Jinin, China happy − Khouribga, Morocco sad − Novocherkassk, Russia happy − Chinhae, Korea, South happy − Rubtsovsk, Russia happy − Syktivkar, Russia happy − San Fernando de Apure, Venezuela strong − Reggio di Calabria, Italy happy − Debrezit, Ethiopia happy − Sao José do Rio Prêto, Brazil happy − Taiyan, China happy − Durg, India weak − Shuangyashan, China happy − Kadhimain, Iraq happy − Xuchang, China happy − Dlepmealow, South Africa happy − Juazeiro do Norte, Brazil happy − Holon, Israel confused − Artux, China happy − Sidi-bel-Abbès, Algeria happy − Bihar Sharif, India happy − Alagoinhas, Brazil strong − Guangshui, 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