Int. J. Environ. Res. Public Health 2020, 17, 1062 5 of 22
3. Methods
3.1. Data Source
As Twitter has been recognized as a popular discussion forum [75] and a social activity platform [76]
for climate issues, we followed the literature [5,8,18] and used tweets to investigate distinct perceptions
of climate issues and evolution on social media. Although Twitter’s ecosystem has been changing
in terms of the number of active users, user demographics, and tweeting conventions in the past
years [77,78], the problem is unavoidable for all the information ecosystems on the Internet. As Twitter
is one of the most popular social websites, we deﬁned our study as characterizing the perception of
climate issues among social media users rather than all the netizens or the whole population.
3.2. Data
In this research, we were interested in tweets containing either #climatechange or #globalwarming,
as these two hashtags exactly correspond to climate change and global warming, respectively, the two
competing deﬁnitions of climate issues. We did not follow [79] to include #AGW (anthropogenic global
warming) as query hashtags in our research because we think that this refers to global warming in
a deﬁned category so cannot be regarded in parallel with the two considered hashtags. We limited the
scope of the search to English-language tweets generated between 1 January 2009 and 31 December
2018. We only collected tweets containing either of the two hashtags in the body of the tweets rather
than those containing these hashtags in the retweeted or quoted text, as we think that retweeted text or
quoted texts cannot directly represent the tweeter’s usage pattern of the two terminologies.
To collect these tweets, we used a Python-based crawler to send requests to the Twitter server to
select hashtags, language, start date, and end date as inputs. Once the ﬁrst request was completed,
the server responded with a ﬁle in json format and the ﬁrst 20 qualiﬁed tweets in a time-descending
order. By parsing the json ﬁle, we obtained a string for the crawler to build the next request and obtain
the next 20 tweets. Thus, a loop was written to keep the crawler sending requests and the crawler
was automatically terminated when all the qualiﬁed tweets publicly available were collected. Our
crawler respected Twitter’s robot.txt and we did not collect, analyze or display any user information in
our study.
Given our goal of exploring the di ﬀerence between the two discourses, the 615,816 tweets
containing both hashtags simultaneously were excluded to di ﬀerentiate between the two datasets
following [67,80]. A total of 6,662,478 tweets were retained, of which 5,774,747 contained #climatechange,
and 887,731 contained “#globalwarming”. The number of qualiﬁed tweets containing #climatechange
and #globalwarming in each year is displayed in Figure 1a.
Int. J. Environ. Res. Public Health 2020, xx, 5 5 of 22
3. Methods
3.1. Data Source
As Twitter has been recognized as a popular discussion forum [ 75] and a social activity
platform [76] for climate issues, we followed the literature [ 5,8,18] and used tweets to investigate
distinct perceptions of climate issues and evolution on social media. Although Twitter’s ecosystem
has been changing in terms of the number of active users, user demographics, and tweeting
conventions in the past years [77,78], the problem is unavoidable for all the information ecosystems
on the Internet. As Twitter is one of the most popular social websites, we deﬁned our study as
characterizing the perception of climate issues among social media users rather than all the netizens or
the whole population.
3.2. Data
In this research, we were interested in tweets containing either #climatechange or #globalwarming,
as these two hashtags exactly correspond to climate change and global warming, respectively, the two
competing deﬁnitions of climate issues. We did not follow [ 79] to include #AGW (anthropogenic