Immigration Station

A Critical discourse analysis of immigration in the 2016 Presidential Election

Through this project, we examined immigration discourse as it related to the 2016 presidential debates. Our goal was to determine how candidates from both sides of the political spectrum coded their language when discussing concepts like immigration reform, amnesty, and legal repercussions. We did this by mining the corpus through manual textual analysis and supplemented our own findings by using collocation and topic modeling tools to identify commonly used words or phrases, and then analyzed these results in terms of our larger data set. Our goal for this project was not to make judgements or draw conclusions based on implicit material; rather, we sought to sort through and present textual data to be used in further research projects.
Within this discourse, we divided up types of immigration based on status, i.e. we specified "illegal" and "legal" immigration. We also associated utterances with certain attitudes, specifically referring to candidates' stances on immigration in pro, anti, and neutral terms. For longer excerpts, we analyzed tropes, identifiying if certain utterances referred to immigration in terms of "values", "security", or "economics". Within those tropes, we specified subtypes, which we unfortunatly did not have sufficient time to consider in our data analysis.



Word Count
people 20
can 14
country 13
need 13
fix 11
million 11
world 11
applause 10
get 10
strategy 9
will 9
legal 8
percent 8
president 8
problem 8


Word Count
people 24
us 15
know 11
need 9
policies 8
coming 7
going 7
one 7
want 7
way 7
applause 6
country 6
now 6
probably 6
can 5


Word Count
president 6
attorney 5
country 5
general 4
us 4
enforce 3
law 3
officers 3
police 3
states 3
time 3
allows 2
back 2
cities 2
done 2


Word Count
think 29
reform 24
will 20
comprehensive 19
get 19
people 17
president 17
want 17
border 15
know 15
said 15
country 12
work 12
good 11
undocumented 11


Word Count
will 27
amnesty 23
going 20
law 19
bill 18
people 18
can 17
illegal 17
know 16
border 15
applause 14
donald 14
problem 14
supported 13
many 12


Word Count
problem 8
25 4
arduous 4
ask 4
border 4
democrats 4
go 4
just 4
meanwhile 4
nothing 4
remains 4
say 4
solve 4
solved 4
will 4


Word Count
donald 8
trump 8
will 6
want 5
hillary 4
million 4
people 4
add 3
apologize 3
based 3
enforcement 3
judge 3
nation 3
said 3
16 2


Word Count
people 4
america 3
want 3
believe 2
can 2
come 2
country 2
doors 2
fact 2
go 2
going 2
just 2
lock 2
look 2
problem 2


Word Count
people 15
applause 10
reform 9
american 8
country 8
need 8
wages 8
can 7
go 7
new 7
america 6
comprehensive 6
economy 6
going 6
us 6


Word Count
marco 11
border 8
defend 8
security 8
think 8
coming 7
country 5
forward 5
opposed 5
us 5
bill 4
deal 4
islam 4
made 4
mistake 4


Word Count
donald 11
trump 10
country 9
said 9
people 8
border 6
criminal 6
just 6
security 6
want 6
aliens 5
american 5
going 5
reform 5
senator 5


Word Count
people 79
going 49
issue 39
will 39
system 33
now 29
american 27
country 24
way 23
years 23
illegal 22
first 21
support 21
control 20
see 19


Word Count
people 15
applause 13
country 13
bill 8
president 8
reform 8
think 8
united 8
know 7
need 6
states 6
will 6
families 5
going 5
hard 5


Word Count
country 20
illegal 17
people 16
said 16
many 15
will 14
think 13
come 11
going 11
say 11
wall 11
just 10
back 9
coming 9
applause 8


Word Count
border 4
actually 3
people 3
america 2
american 2
listened 2
need 2
said 2
secure 2
system 2
abbott 1
acknowledged 1
across 1
amnesty 1
applause 1


Word Count
country 2
family 2
thousands 2
2007 1
actually 1
amendment 1
american 1
bill 1
boat 1
borders 1
camps 1
communists 1
cornell 1
defining 1
dream 1

Although the collocation analysis generated laundry lists of words that were used habitually by the candidates, those lists were abbrebviated by the researchers for a number of reasons. Namely, the number of repetitions associated with words quickly receded as the list grew progressively longer, and a handful of candidates were not in enough debates to permit a substantial data return in regard to their most frequently used terms.

From the lists of words that remain, interesting points still arise in terms of word repetitions and the implications behind the candidates' most frequently used words. For instance, Donald Trump and Hillary Clinton, the two candidates in the general election (and thus two of the candidates with the largest pool of data in our corpus), have distinctly different words at the tops of their lists that mirror surprisingly well their policies and views. Clinton's three most commonly used terms were "think", "reform", and "will," which align well with the overarching themes seen in the Democratic debates and policies. As with many candidates, the need for comphrehensive immigration "reform" was discussed at length by Clinton, with two other future-leaning words assuming the first and third position on her list. With Trump, a candidate who was known for his rhetoric on soveriegnty and strength, used the terms "country", "illegal", and "people" most frequently in his utterances. His most ritually employed term, country, reflects his chief argument on rectifying the resounding issues of illegal immigration -- the need to fortify the American borders and policy against potential erosion from influxes of undocumented immigrants.


We began the topic modeling portion of this project by identifying forty topics with the text-mining tool MALLET. We only took sections in which immigration was discussed into consideration, so as to optimize the topic modelling technology to our central research questions. Thus, we naturally did not consider sections of the debate that were not included in our study. We ultimately launched the program with forty topics because we found that this number provided clear sub-topics within immigration that were relatively easy to identify. We made our own, non-computationally assisted judgements on the topics, so these informed judgement calls are imperfect. Some topics were difficult to decipher or irrelevant to our project (potentially due to the fact that, while we considered any utterance or phrase grouping that included some keyword, those words were used in a host of contexts over the span of all the debates), so we did not include them.

These are the relevant sub-topics, divided into larger topics:
Policy: justice, issues, social welfare, laws
International: terrorism, militay, foreign policy, geopolitics
America First: idealism, middle-class, nationalism
Crime: drugs, gun control
Economy: economic growth, working america, economy/taxes
Other topics included in the discourse related to references to specific candidates, references directly to the presidential race or the debate, and other tangentially related topics including "corporations", "flint crisis", "police brutality", "obamacare", and "women's rights". MALLET was able to sort out these topics from the immigration discourse, but they do not seem directly relevant to this larger project.

Policy: this meta-topic deals with logistics relating to immigration, and the subsequent topics are self-explanatory. All laws relate to overarching immigration policies.

International: Topic six – terrorism – was simple to decipher. Words in this topic included "isis", "war", "radical", and so on. More crucial to our project, "refugees", a category of legal immigrant, also co-occurred with language relating to terrorism. (For the most part, our results found more immigration discourse related to people entering the United States from the southern border.) This shows that it was likely for candidates to discuss refugees and terrorism in the same breath.

America First: Other topics in the analysis related directly to praising the United States, its people, and its values. "Idealism" included words like "greatest", "history", and "future", showing how candidates praised the nation’s accomplishments in a time-specific context. This topic also included “middle-class,” which consisted of words like “people,” "working", and "families", showing how candidates collocated these terms in the same instances. Similarly, "nationalism" collocated words like "americans", "values", and "dream". This data shows the positive, optimistic language candidates used to refer to the nation in which they were running for president.

Crime: The "drugs" topic did not specifically contain words that would normally be associated with immigration. However, it did include words like "brought", referencing cases in which candidates referred to drugs that had been brought across the border, indirectly referencing immigration. The topic "gun control" also seemed to not directly relate to immigration. However, this topic included words like "terrorists", "san", and "bernardino", relating to the 2015 San Bernardino attack, in which ISIS claimed responsibility for two shooters with Middle Eastern heritage. This relates back to the "terrorism" topic, which included the word "refugees".

Economy: This category also related to the "america first" notion of valuing nationalism and the work of middle-class Americans. "Economic growth" included "job" and "cutting", which may refer to jobs that have been filled by immigrants. Similarly, the "working America" included "support" and "americans", and the "economy/taxes" topic included "jobs", "minimum", and "wages", which may refer to immigrant jobs.

Radar Plots
The reason for using radar plots is to have a simple comparison for the number of times candidates use a word. As you can see, there are substantial differences in the language that democratic and republic candidates use.

immigrant undocumented illegal refugee other republican democrat
The specific figures for the amount of times the republican party used immigration terms are:
19 for immigrant
15 for undocumented immigrants
17 for illegal immigrant
31 for refugee
and 38 other terms
The figures for the democrats are as follows:
22 for immigrant
13 for undocumented immigrants
1 for illegal immigrants
19 for refugees
and 5 times for other

These terms are simplified categories for the terms the parties used. Below are all the specific terms the candidates used in the debates.

Immigrant-immigrant(s), Mexican immigrants, American immigrants, Muslim immigrant
Undocumented-undocu. immigrant, undoc. child, undoc. worker, undoc. people, these who were undocumented, and undoc. tomato picker.
Illegal-Illegal immigrant, illegal alien, illegals, and aliens.
Refugee-refugee, syrian refugee, iraqi refugee, and Middle Eastern refugee
Other-Guest worker, people, our neighbors, student, those who live in the shadows

The radar plot evidently shows the republican party spoke immigrant terms more than democrats. In fact, they said these immigrant terms twice the amount of times democrats did: 120 to 60.

immigration border pathway_to_citizenship wall amnesty other republican democrat
Keywords were significant repeated terms that candidates emphasized. Interestingly, amnesty is not used at all by democrats; thus, amnesty is a primary issue in immigration discourse for republicans.

The number for repblicans are:

28 for immigration
107 for border
15 for pathway to citizenship
48 for wall
80 for amnesty
32 for other

The number for democrats are:

49 for immigration
1 for border
10 for pathway to citizenship
10 for wall
0 for amnesty
1 for other

Obviously, the democrats do not generally use the same keywords republicans use. The only 'other' keyword democrats had was 'asylum' which republicans did not use at all. There were many variations of immigration:

immigration reform, immigration bill, immigration policy, immigration laws, immigration visa, comprehensive immigration reform, immigration system, immigration proposal, immigration bashing, immigration law, and immigration problem.

Border had border security, border agent, border patrol and border control.

Wall and amnesty had no variations.

The terms that fell under 'other' were:
birthright citizenship, earned legal status, asylum, e-verify, santuary city, comprehensive reform, and visa overstay.

Republicans used 310 keywords while democrats used 71. In other words, republicans used keywords more than four times the amount compared to democrats.

Democrats used keywords substantially less than republicans even for the same terms. There is margin for error, but overall, the republicans focused on different topics when talking about immigration such as a wall, amnesty, and borders. Democrats are more limited in their discussion of immigration due to their lack of variety in keywords. Both of the radar plots show democrats using the general 'immigrant' and 'immigration' more than republicans despite their lower word count. It can be concluded that republicans tend to differentiate immigrants more than democrats, specifically by legal status and what type of immigrant they are.

Parallel Coordinates

econ value secure Percent Trope Type 21.2 33.3 78.8 66.7 96.4 66.7 3.6

The republicans, naturally red, and democrats, blue, are on a graph which analyzes the relationship between the proportion of trope types they use out of all the debates.
The republicans dominate trope type and they are mostly focused on security in proportion to the other trope types.

econ value secure Percent Trope Type 100 0 25 50 75

This parallel coordinate plot looks at the individual candidates. Some candidates did not show up since they dropped out of running for candidacy and used no tropes in the debate. The two parallel coordinate plots naturally mirror each other, the democratic party uses more tropes on values than security than economy. Republicans are the opposite, they are heavily focused on security and economy rather than values.

Based on our research, we were able to determine that generally, Republican candidates referred to immigration in the 2016 presidential debates more frequently than their Democratic counterparts. The most popular individual terms included: "illegal alien", "illegal", "illegal immigrant", "undocumented ____", "dreamer" "asylum-seeker", "refugee", "migrant", and "guestworker". However, within this discourse, Republican candidates varied their speech to refer to immigration in pro, anti, and neutral terms, referencing specific concepts as diverse as "amnesty" and the proverbial "wall". Some Republican discourse referred to immigrants as "the bad ones" as well as "the good ones", showing a disparity within the party.