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
Daxian, China sad +23.8% − Lisburn, United Kingdom strong +19.9% − Waverley, United Kingdom weak +24.4% − Tarragona, Spain strong +21.8% − PANAMA, Panama strong +3.1% − ROAD TOWN, British Virgin Islands confused +22.0% − Zonguldak, Turkey strong +22.9% − Gurgaon, India strong +14.2% − Warren, United States strong +22.1% − Maiduguri, Nigeria confused +21.6% − Chillán, Chile strong +21.7% − BRIDGETOWN, Barbados confused +23.8% − Pocos de Caldas, Brazil strong +24.0% − Xichang, China confused +20.3% − Vallejo, United States confused +21.9% − Gurgaon, India strong +14.2% − Lubumbashi, Congo, Democratic Republic of the sad +19.0% − Bobo Dioulasso, Burkina Faso angry +20.4% − TIRANA, Albania sad +18.7% − Ubon Ratchathani, Thailand confused +23.5% − Fresno, United States strong +21.7% − Cardiff, United Kingdom strong +16.1% − Hamilton, Canada confused +21.0% − Arad, Romania strong +11.8% − Guilin, China strong +3.0% − Nizhnekamsk, Russia confused +21.0% − Jamalpur, Bangladesh confused +17.7% − Botou, China strong +24.2% − Baranovichi, Belarus strong +18.5% − Kofu, Japan confused +20.9% − Tyumen, Russia strong +7.1% − Zonguldak, Turkey strong +22.9% − Tameside, United Kingdom confused +19.1% − Springfield, United States confused +5.1% − Mulhouse, France happy +21.4% − Vadakara, India sad +6.6% − Engels, Russia strong +21.7% − Ulan-Ude, Russia confused +2.6% − Silay, Philippines happy +19.9% − Pegu, Myanmar confused +24.1% − Cangzhou, China confused +17.7% − Erlangen, Germany confused +22.9% − Diyarbakir, Turkey strong +22.7% − Laval, Canada strong +10.7% − Regensburg, Germany strong +16.0% − Kharagpur, India strong +17.6% − Medellín, Colombia strong +21.8% − The Wrekin, United Kingdom happy +23.6% − Tegal, Indonesia confused +4.6% − Phoenix, United States strong +11.7% − Pohang, Korea, South confused +21.8% − Ambala, India happy +21.8% − Paraná, Argentina strong +12.3% − BASSE-TERRE, Guadeloupe strong +24.8% − Monywa, Myanmar confused +22.1% − Rangpur, Bangladesh happy +24.3% − Surakarta, Indonesia strong +20.9% − Remscheid, Germany strong +19.6% − Ndola, Zambia happy +17.9% − Oberhausen, Germany weak +19.1% − Burgos, Spain strong +19.8% − Sedgemoor, United Kingdom strong +19.3% − The Wrekin, United Kingdom happy +23.6% − Beaumont, United States confused +12.1% − Fukuoka, Japan weak +13.4% − Waitakere, New Zealand confused +23.5% − Pinar del Río, Cuba confused +18.6% − Erbil, Iraq strong +20.1% − Tacoma, United States confused +20.3% − Guarapuava, Brazil strong +18.9% − Mönchengladbach, Germany happy +14.7% − Sikar, India confused +24.6% − Shaoyang, China weak +21.8% − Oberhausen, Germany weak +19.1% − Caruaru, Brazil strong +18.6% − LA HABANA, Cuba strong +18.2% − Engels, Russia strong +21.7% − Várzea Grande, Brazil strong +21.5% − Giza, Egypt confused +23.8% − Mbeya, Tanzania confused +22.8% − Jequié, Brazil strong +5.6% − Malabon, Philippines happy +23.0% − Gaya, India strong +23.6% − Loudi, China weak +17.8% − Yao, Japan strong +22.0% − Ulsan, Korea, South confused +24.5% − Lapu-Lapu, Philippines strong +24.6% − Remscheid, Germany strong +19.6% − Xichang, China confused +20.3% − Chungju, Korea, South sad +4.6% − Grodno, Belarus sad +19.8% − ST. GEORGES, Grenada strong +19.2% − Boksburg, South Africa confused +18.1% − Eastleigh, United Kingdom happy +19.0% − Kure, Japan happy +17.9% − Unnao, India weak +18.8% − Thai Nguyen, Vietnam sad +18.1% − Tacoma, United States confused +20.3% − Huntington Beach, United States strong +23.2% − BISHKEK, Kyrgyzstan weak +8.9% − Tanga, Tanzania confused +20.3% −
Magdeburg, Germany strong -23.7% − Amagasaki, Japan happy -24.2% − Palakkad, India strong -17.6% − San Pablo, Philippines strong -18.3% − Tampa, United States confused -19.1% − Quezon City, Philippines strong -4.0% − Anand, India strong -3.1% − Kawachinagano, Japan happy -22.9% − NOUMEA, New Caledonia strong -18.8% − Alexandria, United States strong -11.9% − Halifax, Canada strong -19.1% − Rouen, France strong -6.3% − Muntinlupa, Philippines strong -19.8% − Chicago, United States strong -18.5% − Yingcheng, China happy -22.9% − Sapucaia, Brazil strong -18.8% − Darlington, United Kingdom strong -24.3% − Jiamusi, China strong -18.6% − Hampton, United States strong -12.1% − Jersey City, United States strong -23.2% − Brescia, Italy strong -18.6% − Dourados, Brazil strong -1.2% − Curitiba, Brazil strong -24.8% − Adana, Turkey confused -23.4% − Petrópolis, Brazil strong -18.6% − Tanjung Balai, Indonesia weak -4.9% − Valencia, Venezuela confused -8.0% − Sefton, United Kingdom strong -5.2% − Cochabamba, Bolivia strong -23.2% − Richmond, United States confused -21.8% − Geelong, Australia confused -2.1% − Gujrat, Pakistan strong -22.0% − Luohe, China happy -22.9% − Mojokerto, Indonesia strong -13.8% − Jinan, China strong -8.9% − San Jose, United States confused -24.0% − Chiba, Japan strong -24.8% − Serra, Brazil strong -5.4% − Sergiev Posad, Russia happy -17.8% − Crewe & Nantwich, United Kingdom strong -17.6% − Manchester, United Kingdom strong -9.2% − Kisumu, Kenya confused -19.7% − Peshawar, Pakistan strong -24.4% − Toluca, Mexico confused -22.6% − Nhatrang, Vietnam happy -22.9% − Batangas, Philippines strong -22.8% − Chimbote, Peru strong -22.8% − Birmingham, United States confused -22.6% − Ingolstadt, Germany strong -14.9% − Bareilly, India confused -23.5% − Gent, Belgium strong -4.2% − Iseyin, Nigeria happy -22.8% − Aguascalientes, Mexico strong -17.6% − Bridgeport, United States strong -18.9% − Leipzig, Germany strong -21.8% − Floridablanca, Colombia strong -22.9% − Richmond, United States confused -21.8% − Kochi, India strong -24.8% − Durango, Mexico strong -25.0% − South Cambridgeshire, United Kingdom strong -17.7% − Braila, Romania strong -17.5% − Fukuyama, Japan strong -22.7% − Sukabumi, Indonesia happy -9.2% − LISBON, Portugal strong -7.5% − Santiago de los Caballeros, Dominican Republic confused -18.9% − Teignbridge, United Kingdom confused -20.2% − Kotte, Sri Lanka confused -1.5% − Zaria, Nigeria confused -18.6% − Irving, United States strong -20.4% − MONROVIA, Liberia happy -23.4% − Kitchener, Canada strong -15.2% − Queimados, Brazil strong -20.4% −
=
Reggio di Calabria, Italy happy − Nasariya, Iraq happy − Sao Joao de Meriti, Brazil happy − Jastrzebie - Zdrój, Poland confused − Sidi-bel-Abbès, Algeria happy − Novocherkassk, Russia happy − Niiza, Japan happy − Bihar Sharif, India happy − Kurume, Japan guilty − Shaown, China happy − Xiaocan, China happy − Moji-Guaçu, Brazil happy − Pinxiang, China happy − Nandyal, India happy − Korla, China strong − Durg, India weak − San Fernando de Apure, Venezuela strong − Rubtsovsk, Russia happy − Sao José do Rio Prêto, Brazil happy − Evpatoriya, Ukraine happy − Jinin, China happy − Khouribga, Morocco sad − Lipetsk, Russia strong − Sirjan, Iran happy − Holon, Israel confused − Juazeiro do Norte, Brazil happy − Basingstoke & Deane, United Kingdom happy − Chinhae, Korea, South happy − Al-Rakka, Syrian Arab Republic happy − Calithèa, Greece happy − Deir El-Zor, Syrian Arab Republic happy − Kashihara, Japan happy − Shanwei, China confused − Colimas, Mexico happy − Taian, China confused − Mudangiang, China happy − Meizhou, China strong − Pórto Velho, Brazil happy − Shuangyashan, China happy − Kiselevsk, Russia happy − Alagoinhas, Brazil strong − Salamanca, Mexico strong − Changweon, Korea, South happy − Angren, Uzbekistan confused − Yuncheng, China weak − Dayuan, China happy − Ferraz de Vasconcelos, Brazil happy − Guangshui, China happy − Xuchang, China happy − Dlepmealow, South Africa happy − Guikong, China happy − Soyapango, El Salvador happy − Chongli, China weak − Taiyan, China happy − Debrezit, Ethiopia happy − Huaiyin, China happy − Syktivkar, Russia happy − Kadhimain, Iraq happy − Kanhangad, India happy − Taldikorgan, Kazakstan happy − Sialkote, Pakistan happy − Artux, 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