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
Fresno, United States strong +21.7% − San Cristóbal, Venezuela weak +18.5% − Baranovichi, Belarus strong +18.5% − Guilin, China strong +3.0% − La Spezia, Italy confused +22.0% − Tegal, Indonesia confused +4.6% − Eastleigh, United Kingdom happy +19.0% − Botou, China strong +24.2% − Thai Nguyen, Vietnam sad +18.1% − Silay, Philippines happy +19.9% − Rangpur, Bangladesh happy +24.3% − Botou, China strong +24.2% − Lisburn, United Kingdom strong +19.9% − Vallejo, United States confused +21.9% − Gurgaon, India strong +14.2% − Regensburg, Germany strong +16.0% − Waverley, United Kingdom weak +24.4% − BISHKEK, Kyrgyzstan weak +8.9% − Anjo, Japan strong +2.2% − LA HABANA, Cuba strong +18.2% − Sikar, India confused +24.6% − Gurgaon, India strong +14.2% − Erlangen, Germany confused +22.9% − Grodno, Belarus sad +19.8% − Ndola, Zambia happy +17.9% − ST. GEORGES, Grenada strong +19.2% − Tangshan, China weak +22.3% − Ichikawa, Japan strong +4.5% − Remscheid, Germany strong +19.6% − Bobo Dioulasso, Burkina Faso angry +20.4% − Engels, Russia strong +21.7% − Amiens, France confused +22.5% − Shaoyang, China weak +21.8% − Surakarta, Indonesia strong +20.9% − Mulhouse, France happy +21.4% − Loudi, China weak +17.8% − Kofu, Japan confused +20.9% − Anyang, China confused +1.0% − Tameside, United Kingdom confused +19.1% − Oberhausen, Germany weak +19.1% − Mönchengladbach, Germany happy +14.7% − Xichang, China confused +20.3% − Pocos de Caldas, Brazil strong +24.0% − Hamilton, Canada confused +21.0% − Abeokuta, Nigeria happy +19.5% − Waitakere, New Zealand confused +23.5% − Jhang, Pakistan strong +23.9% − Maiduguri, Nigeria confused +21.6% − Springfield, United States confused +5.1% − Ubon Ratchathani, Thailand confused +23.5% − Tyumen, Russia strong +7.1% − Gaya, India strong +23.6% − Tacoma, United States confused +20.3% − PANAMA, Panama strong +3.1% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − TIRANA, Albania sad +18.7% − Tarragona, Spain strong +21.8% − Susano, Brazil strong +1.7% − Lapu-Lapu, Philippines strong +24.6% − Malabon, Philippines happy +23.0% − Zonguldak, Turkey strong +22.9% − Huntington Beach, United States strong +23.2% − Yavatmal, India guilty +24.6% − Chillán, Chile strong +21.7% − Warren, United States strong +22.1% − Erbil, Iraq strong +20.1% − Daxian, China sad +23.8% − Tacoma, United States confused +20.3% − San Sebastián, Spain confused +24.0% − Raniganj, India confused +23.2% − Guarapuava, Brazil strong +18.9% − Hachinohe, Japan strong +21.2% − Tanga, Tanzania confused +20.3% − Cardiff, United Kingdom strong +16.1% − Mbeya, Tanzania confused +22.8% − East Hampshire, United Kingdom confused +19.0% − Nizhnekamsk, Russia confused +21.0% − Monywa, Myanmar confused +22.1% − North York, Canada strong +20.2% − Xichang, China confused +20.3% − Arad, Romania strong +11.8% − Medellín, Colombia strong +21.8% − Pinar del Río, Cuba confused +18.6% − Smolensk, Russia happy +17.6% − Kure, Japan happy +17.9% − Ulsan, Korea, South confused +24.5% − The Wrekin, United Kingdom happy +23.6% − Engels, Russia strong +21.7% − Laval, Canada strong +10.7% − Ambala, India happy +21.8% − Remscheid, Germany strong +19.6% − Phoenix, United States strong +11.7% − Diyarbakir, Turkey strong +22.7% − Várzea Grande, Brazil strong +21.5% − Pegu, Myanmar confused +24.1% − Burgos, Spain strong +19.8% − Pohang, Korea, South confused +21.8% − BRIDGETOWN, Barbados confused +23.8% − Fukuoka, Japan weak +13.4% − BASSE-TERRE, Guadeloupe strong +24.8% − Jhang, Pakistan strong +23.9% −
Durango, Mexico strong -25.0% − Toluca, Mexico confused -22.6% − Magdeburg, Germany strong -23.7% − Peshawar, Pakistan strong -24.4% − Cochabamba, Bolivia strong -23.2% − Darlington, United Kingdom strong -24.3% − Crewe & Nantwich, United Kingdom strong -17.6% − Anand, India strong -3.1% − Bareilly, India confused -23.5% − Adana, Turkey confused -23.4% − Irving, United States strong -20.4% − Alexandria, United States strong -11.9% − Brescia, Italy strong -18.6% − Kawachinagano, Japan happy -22.9% − Hampton, United States strong -12.1% − Jiamusi, China strong -18.6% − Geelong, Australia confused -2.1% − Halifax, Canada strong -19.1% − Petrópolis, Brazil strong -18.6% − Bridgeport, United States strong -18.9% − Curitiba, Brazil strong -24.8% − Leipzig, Germany strong -21.8% − Amagasaki, Japan happy -24.2% − Richmond, United States confused -21.8% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Aguascalientes, Mexico strong -17.6% − Kochi, India strong -24.8% − Chicago, United States strong -18.5% − Braila, Romania strong -17.5% − Richmond, United States confused -21.8% − Jinan, China strong -8.9% − San Pablo, Philippines strong -18.3% − Palakkad, India strong -17.6% − Iseyin, Nigeria happy -22.8% − Sapucaia, Brazil strong -18.8% − Tanjung Balai, Indonesia weak -4.9% − Serra, Brazil strong -5.4% − Mojokerto, Indonesia strong -13.8% − Valencia, Venezuela confused -8.0% − Dourados, Brazil strong -1.2% − Gujrat, Pakistan strong -22.0% − South Cambridgeshire, United Kingdom strong -17.7% − Queimados, Brazil strong -20.4% − Yingcheng, China happy -22.9% − Muntinlupa, Philippines strong -19.8% − San Jose, United States confused -24.0% − Zaria, Nigeria confused -18.6% − Sefton, United Kingdom strong -5.2% − Birmingham, United States confused -22.6% − Quezon City, Philippines strong -4.0% − Jersey City, United States strong -23.2% − Manchester, United Kingdom strong -9.2% − Luohe, China happy -22.9% − Kitchener, Canada strong -15.2% − Tampa, United States confused -19.1% − MONROVIA, Liberia happy -23.4% − Floridablanca, Colombia strong -22.9% − Kisumu, Kenya confused -19.7% − Rouen, France strong -6.3% − Batangas, Philippines strong -22.8% − LISBON, Portugal strong -7.5% − Kotte, Sri Lanka confused -1.5% − Nhatrang, Vietnam happy -22.9% − Fukuyama, Japan strong -22.7% − Sergiev Posad, Russia happy -17.8% − Teignbridge, United Kingdom confused -20.2% − Gent, Belgium strong -4.2% − NOUMEA, New Caledonia strong -18.8% − Chiba, Japan strong -24.8% − Chimbote, Peru strong -22.8% − Sukabumi, Indonesia happy -9.2% − Ingolstadt, Germany strong -14.9% −
=
Dlepmealow, South Africa happy − Jinin, China happy − Guikong, China happy − Kashihara, Japan happy − Korla, China strong − Debrezit, Ethiopia happy − San Fernando de Apure, Venezuela strong − Taian, China confused − Guangshui, China happy − Changweon, Korea, South happy − Jastrzebie - Zdrój, Poland confused − Sidi-bel-Abbès, Algeria happy − Rubtsovsk, Russia happy − Dayuan, China happy − Sao Joao de Meriti, Brazil happy − Deir El-Zor, Syrian Arab Republic happy − Nandyal, India happy − Artux, China happy − Sao José do Rio Prêto, Brazil happy − Ferraz de Vasconcelos, Brazil happy − Holon, Israel confused − Kiselevsk, Russia happy − Colimas, Mexico happy − Lipetsk, Russia strong − Shuangyashan, China happy − Evpatoriya, Ukraine happy − Basingstoke & Deane, United Kingdom happy − Chongli, China weak − Taiyan, China happy − Salamanca, Mexico strong − Pinxiang, China happy − Xuchang, China happy − Angren, Uzbekistan confused − Kadhimain, Iraq happy − Soyapango, El Salvador happy − Calithèa, Greece happy − Syktivkar, Russia happy − Pórto Velho, Brazil happy − Sirjan, Iran happy − Shaown, China happy − Alagoinhas, Brazil strong − Durg, India weak − Chinhae, Korea, South happy − Juazeiro do Norte, Brazil happy − Yuncheng, China weak − Nasariya, Iraq happy − Huaiyin, China happy − Taldikorgan, Kazakstan happy − Meizhou, China strong − Mudangiang, China happy − Reggio di Calabria, Italy happy − Al-Rakka, Syrian Arab Republic happy − Shanwei, China confused − Novocherkassk, Russia happy − Moji-Guaçu, Brazil happy − Niiza, Japan happy − Bihar Sharif, India happy − Sialkote, Pakistan happy − Khouribga, Morocco sad − Kurume, Japan guilty − Kanhangad, India happy − Xiaocan, 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