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% − Abeokuta, Nigeria happy +19.5% − Várzea Grande, Brazil strong +21.5% − Chungju, Korea, South sad +4.6% − Burgos, Spain strong +19.8% − Waverley, United Kingdom weak +24.4% − Hachinohe, Japan strong +21.2% − Huntington Beach, United States strong +23.2% − Tangshan, China weak +22.3% − Abeokuta, Nigeria happy +19.5% − Pohang, Korea, South confused +21.8% − Maiduguri, Nigeria confused +21.6% − East Hampshire, United Kingdom confused +19.0% − Mönchengladbach, Germany happy +14.7% − Yavatmal, India guilty +24.6% − Tameside, United Kingdom confused +19.1% − Diyarbakir, Turkey strong +22.7% − LA HABANA, Cuba strong +18.2% − Kharagpur, India strong +17.6% − Ubon Ratchathani, Thailand confused +23.5% − Chungju, Korea, South sad +4.6% − Chillán, Chile strong +21.7% − Gaya, India strong +23.6% − Ambala, India happy +21.8% − Lisburn, United Kingdom strong +19.9% − Remscheid, Germany strong +19.6% − Ndola, Zambia happy +17.9% − Tegal, Indonesia confused +4.6% − Anjo, Japan strong +2.2% − Kure, Japan happy +17.9% − Eastleigh, United Kingdom happy +19.0% − Pegu, Myanmar confused +24.1% − Chon Buri, Thailand strong +23.4% − Hamilton, Canada confused +21.0% − Tarragona, Spain strong +21.8% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Xichang, China confused +20.3% − Waitakere, New Zealand confused +23.5% − Smolensk, Russia happy +17.6% − Yokkaichi, Japan strong +19.6% − Erlangen, Germany confused +22.9% − Cangzhou, China confused +17.7% − La Spezia, Italy confused +22.0% − Gurgaon, India strong +14.2% − Shaoyang, China weak +21.8% − Rangpur, Bangladesh happy +24.3% − Zonguldak, Turkey strong +22.9% − Botou, China strong +24.2% − Ubon Ratchathani, Thailand confused +23.5% − ROAD TOWN, British Virgin Islands confused +22.0% − Phoenix, United States strong +11.7% − TIRANA, Albania sad +18.7% − Medellín, Colombia strong +21.8% − Springfield, United States confused +5.1% − Zonguldak, Turkey strong +22.9% − Kofu, Japan confused +20.9% − BASSE-TERRE, Guadeloupe strong +24.8% − ST. GEORGES, Grenada strong +19.2% − Boksburg, South Africa confused +18.1% − Ulan-Ude, Russia confused +2.6% − Engels, Russia strong +21.7% − Vallejo, United States confused +21.9% − Tacoma, United States confused +20.3% − Bobo Dioulasso, Burkina Faso angry +20.4% − PANAMA, Panama strong +3.1% − The Wrekin, United Kingdom happy +23.6% − Lapu-Lapu, Philippines strong +24.6% − Yao, Japan strong +22.0% − Engels, Russia strong +21.7% − Xichang, China confused +20.3% − Ulsan, Korea, South confused +24.5% − Mbeya, Tanzania confused +22.8% − Jhang, Pakistan strong +23.9% − Surakarta, Indonesia strong +20.9% − Giza, Egypt confused +23.8% − Ichikawa, Japan strong +4.5% − Amiens, France confused +22.5% − Remscheid, Germany strong +19.6% − Guarapuava, Brazil strong +18.9% − Tacoma, United States confused +20.3% − Arad, Romania strong +11.8% − Thai Nguyen, Vietnam sad +18.1% − Piracicaba, Brazil strong +20.7% − Raniganj, India confused +23.2% − Warren, United States strong +22.1% − Sedgemoor, United Kingdom strong +19.3% − Gurgaon, India strong +14.2% − Regensburg, Germany strong +16.0% − North York, Canada strong +20.2% − BRIDGETOWN, Barbados confused +23.8% − Pinar del Río, Cuba confused +18.6% − Loudi, China weak +17.8% − Vallejo, United States confused +21.9% − Oberhausen, Germany weak +19.1% − Vadakara, India sad +6.6% − Sikar, India confused +24.6% − Botou, China strong +24.2% − Tanga, Tanzania confused +20.3% − Pocos de Caldas, Brazil strong +24.0% − Erbil, Iraq strong +20.1% − BISHKEK, Kyrgyzstan weak +8.9% −
Chicago, United States strong -18.5% − Jersey City, United States strong -23.2% − Palakkad, India strong -17.6% − Mojokerto, Indonesia strong -13.8% − Braila, Romania strong -17.5% − Chimbote, Peru strong -22.8% − Cochabamba, Bolivia strong -23.2% − San Pablo, Philippines strong -18.3% − Sukabumi, Indonesia happy -9.2% − Leipzig, Germany strong -21.8% − Richmond, United States confused -21.8% − Rouen, France strong -6.3% − Sergiev Posad, Russia happy -17.8% − Teignbridge, United Kingdom confused -20.2% − Fukuyama, Japan strong -22.7% − Irving, United States strong -20.4% − South Cambridgeshire, United Kingdom strong -17.7% − Tampa, United States confused -19.1% − Quezon City, Philippines strong -4.0% − LISBON, Portugal strong -7.5% − Bareilly, India confused -23.5% − Kotte, Sri Lanka confused -1.5% − Ingolstadt, Germany strong -14.9% − Halifax, Canada strong -19.1% − Amagasaki, Japan happy -24.2% − Gujrat, Pakistan strong -22.0% − Alexandria, United States strong -11.9% − Adana, Turkey confused -23.4% − NOUMEA, New Caledonia strong -18.8% − Kitchener, Canada strong -15.2% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Manchester, United Kingdom strong -9.2% − Durango, Mexico strong -25.0% − Zaria, Nigeria confused -18.6% − Serra, Brazil strong -5.4% − Tanjung Balai, Indonesia weak -4.9% − Magdeburg, Germany strong -23.7% − Floridablanca, Colombia strong -22.9% − Batangas, Philippines strong -22.8% − MONROVIA, Liberia happy -23.4% − Peshawar, Pakistan strong -24.4% − Bridgeport, United States strong -18.9% − Aguascalientes, Mexico strong -17.6% − Birmingham, United States confused -22.6% − Sapucaia, Brazil strong -18.8% − Kisumu, Kenya confused -19.7% − Muntinlupa, Philippines strong -19.8% − Darlington, United Kingdom strong -24.3% − Dourados, Brazil strong -1.2% − Curitiba, Brazil strong -24.8% − Richmond, United States confused -21.8% − Anand, India strong -3.1% − Jiamusi, China strong -18.6% − Chiba, Japan strong -24.8% − Yingcheng, China happy -22.9% − Brescia, Italy strong -18.6% − Sefton, United Kingdom strong -5.2% − Gent, Belgium strong -4.2% − San Jose, United States confused -24.0% − Luohe, China happy -22.9% − Kawachinagano, Japan happy -22.9% − Petrópolis, Brazil strong -18.6% − Valencia, Venezuela confused -8.0% − Iseyin, Nigeria happy -22.8% − Kochi, India strong -24.8% − Geelong, Australia confused -2.1% − Nhatrang, Vietnam happy -22.9% − Crewe & Nantwich, United Kingdom strong -17.6% − Jinan, China strong -8.9% − Hampton, United States strong -12.1% − Toluca, Mexico confused -22.6% − Queimados, Brazil strong -20.4% −
=
Changweon, Korea, South happy − Sao José do Rio Prêto, Brazil happy − Bihar Sharif, India happy − Artux, China happy − Chongli, China weak − Taian, China confused − Huaiyin, China happy − Dlepmealow, South Africa happy − Pinxiang, China happy − Nandyal, India happy − Xuchang, China happy − Meizhou, China strong − Dayuan, China happy − Lipetsk, Russia strong − Mudangiang, China happy − Moji-Guaçu, Brazil happy − Ferraz de Vasconcelos, Brazil happy − Alagoinhas, Brazil strong − Yuncheng, China weak − Nasariya, Iraq happy − Kashihara, Japan happy − Rubtsovsk, Russia happy − Jastrzebie - Zdrój, Poland confused − Debrezit, Ethiopia happy − Taiyan, China happy − Syktivkar, Russia happy − Taldikorgan, Kazakstan happy − Chinhae, Korea, South happy − Guikong, China happy − Sao Joao de Meriti, Brazil happy − Deir El-Zor, Syrian Arab Republic happy − Korla, China strong − Sialkote, Pakistan happy − Juazeiro do Norte, Brazil happy − Shuangyashan, China happy − Pórto Velho, Brazil happy − Kanhangad, India happy − San Fernando de Apure, Venezuela strong − Evpatoriya, Ukraine happy − Jinin, China happy − Al-Rakka, Syrian Arab Republic happy − Colimas, Mexico happy − Basingstoke & Deane, United Kingdom happy − Sidi-bel-Abbès, Algeria happy − Shanwei, China confused − Durg, India weak − Shaown, China happy − Niiza, Japan happy − Calithèa, Greece happy − Kadhimain, Iraq happy − Kurume, Japan guilty − Khouribga, Morocco sad − Reggio di Calabria, Italy happy − Xiaocan, China happy − Sirjan, Iran happy − Salamanca, Mexico strong − Guangshui, China happy − Novocherkassk, Russia happy − Holon, Israel confused − Angren, Uzbekistan confused − Soyapango, El Salvador 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