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A Network Analysis of Foreign Aid Commitments

International Relations scholars often talk about the "diffusion" of norms, behaviors, security worries, etc. throughout the international system. Foreign aid policy is one such norm -- one that developed, democratic countries often are peer-pressured into sharing. But which countries lead the way in terms of aid commitments? Why Network Analysis? The study of networks in the social sciences has largely been restricted to sociology; however, more recently, other fields such as political science (international relations in particular) have adopted network science as a tool in the study of social phenomena. Networks provide a visually intuitive graphical representation of the multiple connections among numerous actors. Aside from being a visually appealing representation of a network of relationships, network analysis of the international system helps to bring to light (and also account for) the fact that international politics is inherently multilateral . Most analyses in
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The Balance of Power between the U.S. and China: Cause for Alarm or Fuel for Alarmism?

It seems a question as old as old as time by this point, but its salience grows with each passing moment: "When will China surpass the U.S.?" And this question inevitably is followed by the question: "And what will that mean for Sino-U.S. relations?" Work by a prominent international relations scholar suggests that, within the context of systemic theory, the international system is a product of the simultaneous activities of individual actors (states) whose individual behavior is prompted by the international system. States work to change the system, which results in change, and this change in turn impels a response by the other actors in the system. Systemic theory, therefore, expects states will engage in active and reactive behaviors -- i.e., if country X increases its arms production, this prompts behavior from country Y who desires to maintain a suitable balance of military capabilities between itself and X. X has introduced change to the system by upset

Do (Should) Rankings of Ph.D. Programs in Political Science Matter?

Not long into the process of working toward a terminal master's degree in political science, I realized I couldn't not pursue a Ph.D. -- the field was too interesting, and (strange as it is) I had come to the realization that I wanted to teach and do research. Once I made this decision and began the process of applying to various programs, my naiveté soon caught up to me. Through discussions with my professors I discovered that all doctoral degrees in political science were not equal, ceteris paribus . To the contrary, the rule of thumb iterated to me was this (more or less): you can only get a job at a university of equal or lesser rank than the school where you earned your Ph.D. Though some might argue this rule of thumb is unfair, it makes some sense; though, it nevertheless alarmed me. While getting a faculty position at an especially prestigious school didn't necessarily concern me, the idea that pedigree could either help or hurt my chances of finding a job did. 

From Positive to Negative "Mass": The Push and Pull Impact of Bilateral Foreign Aid on Bilateral Immigration

I've written before about the impact of foreign aid on immigration , a subject that, to date, hasn't received thorough attention by political scientists, economists, or international political economists. Though the intersection of foreign aid and immigration has gone understudied, a fuller understanding of the consequences the former has for the latter would go a long way in helping policymakers in wealthy donor countries better measure the usefulness of foreign aid as an immigration policy tool. So far, research has shown both that donors use foreign aid to promote development in migrant-sending countries in an effort to reduce the demand for bilateral migration and that migrants residing in donors lobby their host countries to send more aid to their various countries of origin. The impact that foreign aid has on the demand to immigrate, however, has not received much serious consideration by scholars. The Curvilinear Impact of Foreign Investment on Bilateral Migration

The Voice(s) of POTUS: Using the NRC Emotion Lexicon to Predict Topical Prevalence in Donald Trump's Tweets

It's tempting to call President Donald J. Trump the "Tweeter-in-Chief," and this is true for a rather logical reason: the man tweets A LOT. I started compiling a list of the President's tweets -- both from his personal account (@realDonaldTrump) and from his official POTUS account (@POTUS) -- beginning February 16. From that date until now, Trump has tweeted more than 850 times via his personal and POTUS accounts combined. As the below figure shows, aside from a spike in @POTUS tweets during a joint address given by Trump to Congress, Trump's Twitter activity has generally remained steady, and neither his official POTUS account nor his personal account appears to be, in general, more active. However, similar levels of activity do not necessarily guarantee similar degrees influence. Since February 16, both Trump's personal account and the official POTUS account have seen an increase in followers; however, the former has substantially outpaced the latter

The Multiple Voices of Donald Trump

@POTUS and @realDonaldTrump -- the voice of the Trump administration and the voice of Trump himself. Is their a difference between the two? And, if so, what characterizes that difference? The first question can be answered, quite easily, in the affirmative. The answer to the second question is, as the results from an analysis of @POTUS vs. @realDonaldTrump Tweets reveals, dependent on how one defines "difference." The Data The results found via the analysis discussed below are based off of a growing dataset composed of @POTUS and @realDonaldTrump Tweets. The earliest Tweets in the data date to February 16, 2017 with the most recent dated to March 6, 2017. [Note: the program I've been using to collect Tweets reports the time per Tweet several hours in advance of eastern standard time, so the most recent Tweet in the dataset is technically dated to March 7.] The Analysis I used several methods of text analysis to compare @POTUS to @realDonaldTrump Tweets. These incl

"#POTUS" -- A Snapshot into How Twitter Users Feel about the President

Sentiment expressed on social media is far from a scientific poll of the overall population's feelings toward President Trump, but it can offer a valuable measure of expressed attitudes within the online public square. Below are two figures that offer telling insights into current discussion of "#POTUS" among Twitter users as of February 25, 2017 (the day of this writing). Using the NRC Emotion Lexicon in R, I analyzed a dataset of 2,896 Tweets tweeted by 2,455 unique Twitter users that I scraped just this afternoon. [ Note : I'm still collecting more Tweets as I write this post, and it'll take some time before I have a sizable dataset.] The positive vs. negative sentiment score counts per Tweet clearly lean positive. Much of this positive sentiment, as the below figure shows, likely results from a substantial amount of trust that appears in several Tweets that contain #POTUS. While fear , anger , sadness , and disgust all make showings, trust , joy ,