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
Zonguldak, Turkey strong +22.9% − Smolensk, Russia happy +17.6% − Loudi, China weak +17.8% − Kure, Japan happy +17.9% − Erlangen, Germany confused +22.9% − Chillán, Chile strong +21.7% − Waverley, United Kingdom weak +24.4% − Daxian, China sad +23.8% − Springfield, United States confused +5.1% − Várzea Grande, Brazil strong +21.5% − Grodno, Belarus sad +19.8% − Piracicaba, Brazil strong +20.7% − Surakarta, Indonesia strong +20.9% − Hachinohe, Japan strong +21.2% − Jamalpur, Bangladesh confused +17.7% − Ichikawa, Japan strong +4.5% − The Wrekin, United Kingdom happy +23.6% − Kharagpur, India strong +17.6% − ST. GEORGES, Grenada strong +19.2% − Engels, Russia strong +21.7% − Fukuoka, Japan weak +13.4% − The Wrekin, United Kingdom happy +23.6% − BISHKEK, Kyrgyzstan weak +8.9% − LA HABANA, Cuba strong +18.2% − Tameside, United Kingdom confused +19.1% − Rangpur, Bangladesh happy +24.3% − Cangzhou, China confused +17.7% − Remscheid, Germany strong +19.6% − Waitakere, New Zealand confused +23.5% − Pinar del Río, Cuba confused +18.6% − Eastleigh, United Kingdom happy +19.0% − Oberhausen, Germany weak +19.1% − Mönchengladbach, Germany happy +14.7% − Nizhnekamsk, Russia confused +21.0% − Huntington Beach, United States strong +23.2% − Mulhouse, France happy +21.4% − Monywa, Myanmar confused +22.1% − San Cristóbal, Venezuela weak +18.5% − Shaoyang, China weak +21.8% − Cardiff, United Kingdom strong +16.1% − Dunfermline, United Kingdom confused +6.9% − Tarragona, Spain strong +21.8% − Unnao, India weak +18.8% − Oberhausen, Germany weak +19.1% − Botou, China strong +24.2% − Remscheid, Germany strong +19.6% − Raniganj, India confused +23.2% − Mbeya, Tanzania confused +22.8% − Guarapuava, Brazil strong +18.9% − Pegu, Myanmar confused +24.1% − Maiduguri, Nigeria confused +21.6% − ROAD TOWN, British Virgin Islands confused +22.0% − Hamilton, Canada confused +21.0% − Pocos de Caldas, Brazil strong +24.0% − Abeokuta, Nigeria happy +19.5% − Erbil, Iraq strong +20.1% − Silay, Philippines happy +19.9% − Gurgaon, India strong +14.2% − Kofu, Japan confused +20.9% − Ulsan, Korea, South confused +24.5% − Pinar del Río, Cuba confused +18.6% − Guilin, China strong +3.0% − North York, Canada strong +20.2% − Amiens, France confused +22.5% − Ambala, India happy +21.8% − Chon Buri, Thailand strong +23.4% − Sikar, India confused +24.6% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Yavatmal, India guilty +24.6% − San Sebastián, Spain confused +24.0% − Ndola, Zambia happy +17.9% − Burgos, Spain strong +19.8% − Medellín, Colombia strong +21.8% − BASSE-TERRE, Guadeloupe strong +24.8% − Boksburg, South Africa confused +18.1% − Ubon Ratchathani, Thailand confused +23.5% − Warren, United States strong +22.1% − Giza, Egypt confused +23.8% − Botou, China strong +24.2% − Lapu-Lapu, Philippines strong +24.6% − Jhang, Pakistan strong +23.9% − East Hampshire, United Kingdom confused +19.0% − Arad, Romania strong +11.8% − Engels, Russia strong +21.7% − Xichang, China confused +20.3% − Tanga, Tanzania confused +20.3% − Sedgemoor, United Kingdom strong +19.3% − Malabon, Philippines happy +23.0% − Phoenix, United States strong +11.7% − Jhang, Pakistan strong +23.9% − Susano, Brazil strong +1.7% − Tyumen, Russia strong +7.1% − Tacoma, United States confused +20.3% − Diyarbakir, Turkey strong +22.7% − Jequié, Brazil strong +5.6% − BRIDGETOWN, Barbados confused +23.8% − Xichang, China confused +20.3% − Thai Nguyen, Vietnam sad +18.1% − Bobo Dioulasso, Burkina Faso angry +20.4% − Pohang, Korea, South confused +21.8% − Gaya, India strong +23.6% −
Jinan, China strong -8.9% − LISBON, Portugal strong -7.5% − San Jose, United States confused -24.0% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Palakkad, India strong -17.6% − Floridablanca, Colombia strong -22.9% − Alexandria, United States strong -11.9% − Chicago, United States strong -18.5% − Luohe, China happy -22.9% − Yingcheng, China happy -22.9% − Richmond, United States confused -21.8% − Bridgeport, United States strong -18.9% − Birmingham, United States confused -22.6% − Fukuyama, Japan strong -22.7% − Teignbridge, United Kingdom confused -20.2% − Anand, India strong -3.1% − Hampton, United States strong -12.1% − Kotte, Sri Lanka confused -1.5% − Muntinlupa, Philippines strong -19.8% − Richmond, United States confused -21.8% − Kawachinagano, Japan happy -22.9% − Chimbote, Peru strong -22.8% − Kisumu, Kenya confused -19.7% − MONROVIA, Liberia happy -23.4% − Queimados, Brazil strong -20.4% − Tanjung Balai, Indonesia weak -4.9% − Kitchener, Canada strong -15.2% − Zaria, Nigeria confused -18.6% − Tampa, United States confused -19.1% − Rouen, France strong -6.3% − San Pablo, Philippines strong -18.3% − Valencia, Venezuela confused -8.0% − Sefton, United Kingdom strong -5.2% − Amagasaki, Japan happy -24.2% − Quezon City, Philippines strong -4.0% − Bareilly, India confused -23.5% − Serra, Brazil strong -5.4% − Gent, Belgium strong -4.2% − Kochi, India strong -24.8% − NOUMEA, New Caledonia strong -18.8% − Sapucaia, Brazil strong -18.8% − Sukabumi, Indonesia happy -9.2% − Braila, Romania strong -17.5% − Iseyin, Nigeria happy -22.8% − Gujrat, Pakistan strong -22.0% − Toluca, Mexico confused -22.6% − South Cambridgeshire, United Kingdom strong -17.7% − Peshawar, Pakistan strong -24.4% − Adana, Turkey confused -23.4% − Aguascalientes, Mexico strong -17.6% − Mojokerto, Indonesia strong -13.8% − Leipzig, Germany strong -21.8% − Sergiev Posad, Russia happy -17.8% − Batangas, Philippines strong -22.8% − Manchester, United Kingdom strong -9.2% − Dourados, Brazil strong -1.2% − Jersey City, United States strong -23.2% − Crewe & Nantwich, United Kingdom strong -17.6% − Jiamusi, China strong -18.6% − Curitiba, Brazil strong -24.8% − Chiba, Japan strong -24.8% − Magdeburg, Germany strong -23.7% − Irving, United States strong -20.4% − Halifax, Canada strong -19.1% − Nhatrang, Vietnam happy -22.9% − Petrópolis, Brazil strong -18.6% − Geelong, Australia confused -2.1% − Ingolstadt, Germany strong -14.9% − Darlington, United Kingdom strong -24.3% − Brescia, Italy strong -18.6% − Cochabamba, Bolivia strong -23.2% − Durango, Mexico strong -25.0% −
=
Reggio di Calabria, Italy happy − Kashihara, Japan happy − Salamanca, Mexico strong − Bihar Sharif, India happy − Shanwei, China confused − Artux, China happy − Sidi-bel-Abbès, Algeria happy − Lipetsk, Russia strong − Kanhangad, India happy − Rubtsovsk, Russia happy − Shaown, China happy − Dlepmealow, South Africa happy − Xiaocan, China happy − Xuchang, China happy − Changweon, Korea, South happy − Juazeiro do Norte, Brazil happy − San Fernando de Apure, Venezuela strong − Meizhou, China strong − Korla, China strong − Niiza, Japan happy − Sao Joao de Meriti, Brazil happy − Kadhimain, Iraq happy − Khouribga, Morocco sad − Taian, China confused − Durg, India weak − Angren, Uzbekistan confused − Basingstoke & Deane, United Kingdom happy − Deir El-Zor, Syrian Arab Republic happy − Mudangiang, China happy − Sialkote, Pakistan happy − Evpatoriya, Ukraine happy − Kiselevsk, Russia happy − Ferraz de Vasconcelos, Brazil happy − Novocherkassk, Russia happy − Moji-Guaçu, Brazil happy − Al-Rakka, Syrian Arab Republic happy − Jinin, China happy − Pinxiang, China happy − Dayuan, China happy − Holon, Israel confused − Yuncheng, China weak − Guangshui, China happy − Pórto Velho, Brazil happy − Syktivkar, Russia happy − Nasariya, Iraq happy − Calithèa, Greece happy − Jastrzebie - Zdrój, Poland confused − Shuangyashan, China happy − Guikong, China happy − Colimas, Mexico happy − Kurume, Japan guilty − Debrezit, Ethiopia happy − Sirjan, Iran happy − Nandyal, India happy − Taiyan, China happy − Chinhae, Korea, South happy − Huaiyin, China happy − Chongli, China weak − Soyapango, El Salvador happy − Taldikorgan, Kazakstan happy − Alagoinhas, Brazil strong − Sao José do Rio Prêto, Brazil 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