Mining web-based data to assess public response to environmental events

Environmental Pollution

Volumn 198, Issue , 2015, Pages 97-99

  Cha, YoonKyung ^a   Stow, Craig A ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

Algal blooms; Data mining; Google trends; Public perception and interest; Social media; Twitter; Web search trends

Indexed keywords

ENVIRONMENTAL MANAGEMENT; LAKES; POTABLE WATER; SOCIAL NETWORKING (ONLINE); WATER SUPPLY; WEBSITES;

CYANOBACTERIA BLOOMS; ENVIRONMENTAL ACCIDENTS; ENVIRONMENTAL ISSUES; GOOGLE TRENDS; HARMFUL ALGAL BLOOMS; MICROCYSTINS; PUBLIC PERCEPTION; WEB CONTENT;

WATER TREATMENT;

CYANOBACTERIA;

MICROCYSTIN;

ALGAL BLOOM; CYANOBACTERIUM; DATA MINING; INTERNET; LAKE; POLLUTION; PUBLIC OPINION; STATISTICS AND NUMERICAL DATA; UNITED STATES; WATER MANAGEMENT; WATER POLLUTION; WATER SUPPLY;

CYANOBACTERIA; DATA MINING; ENVIRONMENTAL POLLUTION; HARMFUL ALGAL BLOOM; INTERNET; LAKES; MICROCYSTINS; OHIO; PUBLIC OPINION; WATER POLLUTION; WATER PURIFICATION; WATER SUPPLY;

EID: 84938718512     PISSN: 02697491     EISSN: 18736424     Source Type: Journal    
DOI: 10.1016/j.envpol.2014.12.027     Document Type: Article

References (9)

1. Brookes, J.D., Carey, C.C., Resilience to blooms. Science 334 (2011), 46–47.
2. Daume, S., Albert, M., von Gadow, K., Forest monitoring and social media – complementary data sources for ecosystem surveillance?. For. Ecol. Manag. 316 (2014), 9–20.
3. Hampton, S.E., Strasser, C.A., Tewksbury, J.J., Gram, W.K., Budden, A.E., Batcheller, A.L., Duke, C.S., Porter, J.H., Big data and the future of ecology. Front. Ecol. Environ. 11 (2013), 156–162.
4. Kelling, S., Hochachka, W.M., Fink, D., Riedewald, M., Caruana, R., Ballard, G., Hooker, G., Data-intensive science: a new paradigm for biodiversity studies. Bioscience 59 (2009), 613–620.
5. Laney, D., 3D Data Management: Controlling Data Volume, Velocity and Variety. META Group Research Note 6, 2001.
6. Paerl, H.W., Huisman, J., Blooms like it hot. Science, 320, 2008, 57.
7. Proulx, R., Massicotte, P., PÉPino, M., Googling trends in conservation biology. Conserv. Biol. 28 (2014), 44–51.
8. Reichman, O., Jones, M.B., Schildhauer, M.P., Challenges and opportunities of open data in ecology. Sci. (Washington) 331 (2011), 703–705.
9. Zhao, Y., R and Data Mining: Examples and Case Studies. 2012, Academic Press, San Diego.