In researchers methods rather than results is sometimes

In conclusion, statistical testing showed the three sources environmental
and mainstream sources were already influenced by code frequencies. After data
was close fully inspected from” both code-level bar charts and article-level
nonmetric multidimensional scaling plots showed that the selected
environmentalist source more strongly emphasized water supply scarcity, aquatic
life besides fish, endangered species, and motivations not contingent on use.”
(Weber2017) The mainstream news sources showed water quality and recreational
motivations. The research also showed that publication dates were insignificant
in testing attributes and motivations. Over, the paper was published to show
other researchers methods rather than results is sometimes the answer. The writers
didn’t find much information using consent analysis to match the level of
detail put forth. “We ultimately
succeeded in drawing on the advantages of both qualitative and quantitative
traditions, thanks to an interdisciplinary team, with much effort toward
careful sample design, manual coding, and the benefit of specialized
visualization and statistical methods. Even so, our codebook detail pushes the
limit of manual content analysis. Vast research possibilities exist with online
data, and we hope our method opens doors for quantitative analysis of
qualitative data, for investigators having the necessary human resources but
limited research dollars.” (Weber2017)

The first set of results were produced through extensive amounts of coding
during the pilot phase. The data is spread between five tables, six figures and
three appendixes. The words fish, wildlife and water quality “Out of 19
attributes represented in the table, were more than one third of the 368
co-occurrences.” (Weber2017) The pilot was done to remove all differences for
common codes since one thing could be placed into multiple categories. Categories
such as consumptive use, non-consumptive use, and not use contingent
motivations were put into place.

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The methods used in researching were sampling, coding, visualization and
statistical analyses. The sampling decision was made to avoid bias by using
different materials written and audience diversity. “The coding approach was
rigorously tested in a pilot phase, with measures developed to ensure high data
quality, including use of two independent coders.” (Weber2017) In addition to
attributes, such as flooding, water quality characteristics, and wildlife, motives
like recreation and pollution prevention were also coded. Coding also played a
part in creating the visual aids such as bar charts, box plots, “nonmetric
multidimensional scaling plots” as well as a separate “two-dimensional NMS
plots for attribute and motivation code frequencies.” “This technique is
especially useful for visualizing clusters of similar data points and has been
used in ecology to discern similar species distributions for various field
sites.” (Clarke 1993)


Ecosystem services is a collaborative grouping system in science, that’s
responsible for surveying the relationship between human welfare and
environmental management. While ecosystem service research has become common, a
small amount of effort is made toward narrowing down valuable information
wanted in direct relationship to people and their ecosystem. The data collected
on the following attributes were from environmental and mainstream text from
the New York Times, National Geographic, and The Wall Street Journal. This decision
was made to avoid bias ultimately showing bias by picking these three specific
news companies, However. This ultimately showed difference in materials written
and audience diversity. This research singly focuses on flooding, water quality
characteristics, and wildlife while using content analysis to collect data over
a multiyear timeline showing the frequency of the searched topics and relevance
an article has on individual’s wellbeing. The topics addressed are” (1)
Document the range and relative frequency of attributes and motivations used in
texts to represent stream ecosystems and human interest in them; (2) Test
whether attributes and motivations vary by publication source or date, and; (3)
Test associations between defined categories of attributes and motivations.” (Weber2017)