Background

Bitcoin is a type of digital currency started in approximately 2009 by a forerunner in Japan. The digital currency is unlike physical cash as it manifests as a sequence of code in a distributed ledger system called a blockchain.
The appeal of the blockchain, and the so called “crypto” currencies, is that the mechanism where transactions are recorded is in a cryptographic “linked list” that is distributed through a network of nodes around the world. The design is thought to ensure security, privacy, redundancy as every node has a copy of the transaction, and a distributed way of operating rather than centralizing resources in one location. Individual coins can be stored in a “secure wallet” or converted to another currency (for example US Dollars, British Pound, etc) via exchanges.
 This means that the appeal of such a crypto currency may be global, an effort to perhaps create a currency that can be exchanged into local/regional currencies as needed. From the perspective of urban science, this is an interesting phenomena as cities around the world not only are empowered to create their own regulations/rules concerning treatment of bitcoin, consequently providing differentiation or competition in the marketplace for attracting potential startups as well as financial investment. Additionally, some cities may even opt to transition to some form of digital currency in the future as geopolitical, economic, climate, and other events destabilize local currencies, as in the case of popular usage of bitcoin in places like Venezuela, where it is reported that a portion of the population has embraced bitcoin over the devalued local currency or as in the case of Japan, where it has been adopted by the government as a currency [10].  
The drawback to the design is that like most things, it can be exploited both from a profitability perspective as several exchanges, and other service providers, have been hacked, as well for non-positive consequences. Additionally, given that there is no physical cash equivalent by default, and the newness of this currency, regulators have been deliberating on how exactly to craft the rules of the game pertaining to any regulatory requirements.
For example, according to the Internal Revenue Service, bitcoin is considered an asset rather than a currency. Meanwhile the New York State Department of Finance has issued its own set of rules and regulations in regards these financial transactions that are serviced by companies operating in the state.
Ironically, as the popularity and novelty of the phenomena grows, bitcoin or crypto currencies in general are becoming a financial instrument – that is another alternative to invest in from the perspective of financial markets.  
The rise and popularity of has also attracted a number of “heists”, with the latest incident concerning a service provider [1].  Another avenue of skepticism is that the rapid rise of prices for a single bitcoin – may indicate a speculative “bubble”, where the price of a good is over-valued and may burst at any point[2].
Indeed, despite the relative newness of the technology, the concerns around potential weaknesses of the system, the two board of trades in Chicago recently announced that options trading will proceed [3]. This landmark announcement suggests that the boards of trade are in effect making policy decisions that not only legitimize the currency as a financial instrument for the purpose of investing by the greater (professional) investment community, it also suggests that cities and states are capable of defining the policies that dictate how this digital currency or asset class will be dealt with and in turn affect which coin based business are attracted to or dissuaded from operating in various locations.

 Update on Adjusted Scope to Address Reviewer Feedback  

The original idea for this exploratory study was to utilize natural language processing techniques to compare news reporting on bitcoin across four newspapers The L.A. Times, The Chicago Tribune, The Washington Post, and the New York Post that are published in four distinct US cities Los Angeles, Chicago, Washington DC, and New York City, to determine if there were any differences in the type of reporting on the topic.
To address feedback from the review provided, the exploratory study was scaled down to focus on just one publication – The New York Post, and the exploration was limited to word frequency, author frequency, and time frequency of publication.
In the next study, I would like to extend this include sentiment analysis in order to conduct statistical tests on differences across time, author and publications/cities and graph visualization for the network or connections amongst the sub-topics/words covered in the articles. Likewise future iterations, I would like to compare different types of newspapers within the city as well – for example Wall Street Journal, New York Times, NY Daily News, NY Post – as each targets a specific demographic both from a literacy perspective and socioeconomic background.  

 Data

The 75 articles containing the term “bitcoin” were collected from LexisNexis and WorldNews Access from the New York Post, covering a period of May 31, 2015  - Dec 8, 2017. The data concerning author, article title, word count, publication date, newspaper section, and city were preserved in a pandas data frame. There were twenty-two unique authors not including “staff” or the wire services like Associated Press or Reuters; based on the names it appears that both male and female writers contributed articles on the topic.   

Methodology

News articles were collected from NYU’s databases – LexisNexis and World News Access with the search term “bitcoin” published in the daily newspaper the New York Post. This newspaper was selected as the first one to pilot to see how the “popular” press reports coverage on the topic. In a following study, I would like to contrast this to newspapers that publish economic analysis as well as “daily news”, for example the New York Times and the Wall Street Journal both with headquarters in New York and Financial Times based out of London, amongst others.
In exploring the variety of authors on the subject, a frequency distribution was plotted in matplotlib based on author counts. The most frequent author was by far Kevin Dugan.  Additionally a table was displayed to show number of articles by author.  
Next, an exploration of the frequency of articles published by month was explored and visualized in a matplotlib plot. The months with the greatest number of articles were at the end of year, comprising October, November, and December. As this data set spans almost two years, it seems plausible that perhaps more coverage of bitcoin occurred towards the end of the year.
Results
In regards to authorship of articles in the New York Post during the timeline of May 31, 2015  - Dec 8, 2017, a handful of authors are the most frequent writers of articles on the topic.  This may reflect work assignments as directed by a particular department/desk, or perhaps expertise in a particular area. One benefit of having consistent authors on a particular topic suggests that an analysis of not only a publication in a given city, but also the authors in particular cities can identify perhaps the nuances that build up from the personal author’s , to the publication, to the eventual city perspective. In future work, this could be analyzed further. At present the top five authors by number of contributions on bitcoin to the NY Post are Kevin Dugan, John Crudele, Laura Italiano, James Covert, and “Post Staff” ( it should be noted that not all articles have an author identified). Matplotlib figure follows below with a frequency distribution.