As the Citizen Science Research Intern at Caravan Studios, I was tasked to explore the air pollution discourse online for Poland, the EU country with the worst air pollution record. My aim was to 1) gain a temporal and spatial understanding of the interest about air pollution in Poland and 2) have a sense of the popular discourse about air pollution. To expand on the latter: how did Poles express themselves about air pollution (whom did they blame, how did they describe the impact of pollution on daily life etc.).
I investigated different social media sources, including: Twitter, Facebook, Reddit, Wykop, NK.pl, and Google Trends. Here's the summary of my outputs per sources below:
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Google Trends: I was able to generate charts showing browsing frequency over the last 5 years, using a set of keywords relevant to the subject of air pollution. Additionally I was able to compare the frequency of those searches between the whole of Poland and the southwestern region of Lesser Poland, known to be the region heavily impacted by smog.
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Facebook: Due to changes in Facebook's API, I was unable to query for meaningful content. I considered a web scraping approach but Facebook browsing features limits to 5 posts over a narrow time period. Thus I dropped the site from my inquiries.
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Reddit: I made a post on r/Polska, the Polish Subreddit, soliciting inputs about air pollutions from Polish individuals directly. I was able to gather over half a dozen responses. The objective of my sollicitation was to inform my research process and use local testimonies to cross-examine with news story and subsequent data I gathered.
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NK.pl: A Polish forum site, which I rapidly found to be lacking in the content I was researching. Futhermore a poster on r/Polska kindly informed me that "NK.pl is dead".
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Twitter Analytics: Using the Twitter's API, I queried Tweets from the last 7 days (a limitation of the public access API) geotagged to Poland with the mention of smog. Although the scope of temporal granularity is quite limited, the API nonetheless provides a snapshot of the "current discourse". I was able to both generate a timeseries and word clouds from the Tweets collected.
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Wykop: The "Polish Reddit". Wykop was my richest source of information: I was able to scrape over 7,000 posts, dating as far back to 2012, mentioning smog. I was able to generate a timeseries of the frequency of the posts, in addition to a word cloud.
