I am collecting data on #nobannowall to observe the reactions of @POTUS policies and executive orders on immigrants and refugees.
Growing up in the Rust Belt in a community where nearly every adult worked in a factory and being raised by refugees, I am in ways connected to both the anti and pro-refugee and immigrant movement. #Nobannowall reflects upon conflicting and sometimes, confusing sentiments in my hometown, including resentment towards new immigrants who were trying to compete for the fewer number of factory jobs and support from those who believe that a growing immigrant population will halt decline in the city. Analyzing #nobannowall requires the recognizing of the stories of decline and the desire for Americentric policies while understanding why Americans still support immigrants despite decline.
I assumed that most of the tweets would express disapproval of the recent U.S. travel ban against the seven dominantly Muslim countries. Most of the tweets did express disapproval of this executive order and specifically mentioned Muslims (using hashtags calling the executive order a #MuslimBan) and demonstrated support for “immigrants” and “refugees.” Surprisingly, almost no tweets mentioned the wall between the U.S.-Mexican border that Donald Trump intends to build. Overall, the tweets did not explain what the policy was or specially who was affected, but more so, expressed people’s feelings towards immigrants and refugees. For example, @RepKihuen was retweeted “@POTUS I was once undocumented – now, I’m a member of Congress. #NoBanNoWall” and @SouthernDems_ retweeted @TheDemocrats: RT to remind Trump that he has no mandate to carry out his unconstitutional, immoral Muslim ban. #NoBanNoWall https://t.c…” Tweets such as these do not provide much context: Why is the executive order unconstitutional? Who is affected? I returned to continue working on the lab six hours after running TAGS and am surprised that there were only 2,364 tweets with this hashtag since I am overloaded by the number of tweets on the topic on my personal wall. There doesn’t seem to be one account that is using the hashtag either, indicating perhaps that the hashtag is used widely.
Stories quoting #nobannowall tended to report on anti-travel ban movements and protests across the U.S. while stories on the topic of the travel ban and the proposed U.S.-Mexican border wall focused on the describing how the Trump administration was handling the immigrant “crisis.” One story quoting #nobannowall discussed the widespread protests across the U.S. while another story reported on celebrity models whose mother is an immigrant participating in a protest in New York City. The environment was mostly anti-Trump, expressing perhaps that #nobannowall was used mostly by Trump dissenters. I found more articles on the proposed U.S.-Mexican border wall when I searched the topic of immigrants than I did the hashtag, demonstrating perhaps that though the story was covered by major media outlets, Twitter users were more concerned about the travel ban aspect of the hashtag.
Ten years ago, all of the rhetoric on immigration focused on illegal immigrants especially those of Hispanic background. It also centered around the economic implications of such immigration and less on the danger or potential terrorism threats that the U.S. would face. Unlike today, there was no mention of “religion” or even, “political” situations in countries where immigrants originated from; however, the idea that immigrants are here in the U.S. to only “secure a better future” remains the top counterpoint to anti-immigration policies. I found it surprising that the crackdown of illegal immigration started long before Trump proposed a “wall” along the U.S.-Mexican border. In one of my historical articles, Federal agents were criticized for luring illegal workers by requiring them to participate in a health and safety information session. Health advocates became concerned that illegal immigrants would avoid health clinics and worker safety sessions in the future. In another article, the author discussed the economic implications of illegal immigrants – they often contribute to the U.S. economy by working for low wages and spending money in the U.S. while some cost the government a lot for incarceration and receiving certain benefits.
The process that I conducted aimed to capture the different temporal “envelopes” of the issue which is needed to connecting to the liveliness of the issue. Scraping tweets allowed me to follow the issue in minute by minute moments while reading articles allowed me to understand the issue within a longer time frame – from a week to as long as ten years. Each step helped me “stabilize” the issue. However, I felt that the TAGS program and the reading of articles from different days was not enough. Marres and Welteverde discussed that scraping software often include more data analysis features (ex. word frequency. Even though I tried hard to skim through all of the tweets, my brain could not process all of the tweets to develop extremely detailed analysis.
Works Cited
Articles on #nobannowall
Bacon, John. 2017. “Protests against Trump’s immigration plan rolling in more than 30 cities.” USA Today, February 1. http://www.usatoday.com/story/news/nation/2017/01/29/homeland-security-judges-stay-has-little-impact-travel-ban/97211720/
Tietjen, Alexa. 2017. “Gigi and Bella Hadid join the #NoBanNoWall march in NYC.” Los Angeles Times, February 1. http://www.latimes.com/fashion/la-ig-hadid-sisters-protest-20170130-htmlstory.html
Articles on topic
Blake, Aaron. 2017. “The Trump team bizarrely quibbles with calling its travel ban a ‘ban’ – and then backs down.” Washington Post, February 1. https://www.washingtonpost.com/news/the-fix/wp/2017/01/31/trumps-team-is-mad-people-are-calling-the-travel-ban-a-ban-even-though-they-also-called-it-a-ban/?utm_term=.10911c8787ad
2017. “Can Trump Make Mexico Pay For the Wall? Not The Ways That He And The GOP Are Considering.” Fortune, January 31. http://www.forbes.com/sites/beltway/2017/01/31/can-trump-make-mexico-pay-for-the-wall/#57009ad663cd
Historical articles
Greenhouse, Steven. 2006. “U.S. Officials Defend Ploys to Catch Illegal Immigrants.” New York Times, February 11. http://www.nytimes.com/2006/02/11/us/us-officials-defend-ploys-to-catch-immigrants.html
Hanson, Victor Davis. 2006. “Analyzing illegal immigration.” Chicago Tribune, March 31. http://www.chicagotribune.com/news/opinion/chi-0603310310mar31-story.html
Reading
Marres, Noortje, and Esther Weltevrede. 2013. “Scraping the Social?” Journal of Cultural Economy 6 (3): 313–35.
Excellent work Jennifer! I too am surprised that the hashtag #nobannowall seemed to be focused on the #noban aspect, and not really on the #nowall side. This was a very insightful observation and showed that you carefully inspected the data you gathered. I think that one reason the hashtag focused around tweets about the Muslim ban is the recency of the ban itself. Perhaps you can look next week and see if more wall tweets come out once the virtual dust has settled around the muslim ban. This post shows me that people are vocally protesting the muslim ban and voicing their discontent at the new regime. Perhaps the Trump team should run a couple of their hashtags thru the data scraper, and they can get a good feel for what people are thinking/saying. Your post is almost in stark opposition to my hashtag, because the majority of your data is anti Trump/Trump’s policies, and mine are majorly for him.
…are in the majority for him.
Great work collecting and analyzing the first couple thousand tweets Jennifer. I enjoyed reading about how you have a personal connection to this topic, and how you are connected to both sides of the discussion. I am not surprised about the focus on the muslim ban from your hashtag as it is the more relevant topic being discussed currently. I would not be surprised if the ban will be the topic of discussion for months to come unless there are some policy changes regarding the wall. I am curious how this tweet will play out in the coming weeks as well with the upcoming decision about Trump’s ban.