How Language Structure Affects Language Persistence: examined through the rise and fall of Latin and the Roman Empire
Kyurhee Kim
Abstract
In general, we believe that Latin, the official language of Rome, spread widely with the birth of the Roman Empire, and naturally disappeared with the fall of the Roman Empire. Was the rise and fall of Latin a natural consequence of the rise and fall of the Roman Empire? Rather, could it be that Latin was the reason why Rome was able to grow into an empire, and was also the reason why Rome fell?
If the characteristics and structure of language can influence the thinking and behavior of people who speak the same language, this means that a society (or nation) composed of such people will ultimately be influenced by the characteristics and structure of language. Through this study, I attempted to analyze this influence of language through the characteristics and structure of Latin.
As the official language of the Roman Empire, Latin follows strict grammatical rules and is known as a formal style language that can express complex concepts precisely. It is assumed that these characteristics of Latin contributed greatly to Rome’s growth into an empire through wars of conquest by efficiently operating its military command and legal system. To test this guess, I set up hypothesis 1 as follows.
- Hypothesis 1: Latin and its formality would have been advantageous to the early Roman Empire in expanding its territory.
However, after Rome grew into a multi-ethnic world empire that spoke various languages across a vast territory, this strictness of the Latin language actually hindered free communication between different ethnic groups within the empire, making social integration of the Roman Empire difficult. It can be assumed that this may have been one of the causes of the fall of the Roman Empire. To test this conjecture, I also set up Hypothesis 2 as follows.
- Hypothesis 2: The strict formality of Latin may have been an obstacle to Rome’s ability to embrace diverse peoples and cultures after it became a great empire that ruled most of continental Europe.
To test Hypothesis 1 and Hypothesis 2, I conducted a case study comparing Latin and English. As a result of the analysis, Latin was found to be relatively more efficient than English in operating the military command system and legal system with precise expression according to strict grammatical rules. This is an analysis result that supports Hypothesis 1, which states that the strictness of Latin helped Rome grow into an empire. However, due to Latin’s excessive strictness, it has less flexibility in linguistic expressions, such as nuances, than English, and was analyzed to be ineffective in managing a global empire composed of multi-ethnic groups. This is an analysis result that supports Hypothesis 2, which states that the strictness of the Latin language may actually hinder the management of the Roman Empire, which grew into a global empire.
Through this study, I analyzed through case studies that the linguistic characteristics and structure of Latin may be one of the causes that influenced the rise and fall of the Roman Empire. Rather than viewing the rise and fall of Latin as a natural consequence of the rise and fall of the Roman Empire, I think it is an interesting point of this study that the linguistic characteristics and structure of Latin were analyzed as one of the main causes of the rise and fall of the Roman Empire.
When and What Do People Read?
Kyurhee Kim
Abstract
I have been interested in books since I was young, so my dream is to publish my own book someday. So I wanted to know if the amount of books people read change by month. And also, I wanted to know when fiction is sold a lot, nonfiction is also sold a lot. The best way to do this analysis is to analyze the total monthly sales of fiction and non-fiction, but unfortunately, data on total sales was not available. So, as an alternative, I used a newspaper’s bestseller section for analysis. I thought that a book listed in the bestseller section meant that it sold a lot because a lot of people read it. I decided that if I could know the number and ratio of fiction and non-fiction books added each month among bestsellers, I could analyze monthly or seasonal trends about what types of books people prefer and read a lot each month.
Specifically, analysis data was obtained from the bestseller section of the New York Times, a representative bestseller list. The New York Times bestseller list has two genres: fiction and nonfiction, each containing 15 best-selling books ranked from 1st to 15th. I counted the number of new books added in both genres from November 2019 to October 2020 and used that for my analysis.
As a result of analyzing the number of new best-selling books in fiction and nonfiction by month, the averages for fiction and nonfiction were 15.83 and 11.58, respectively. This means that 15 to 16 fiction books and 11 to 12 nonfiction books are newly registered on the bestseller list every month. The maximum value for fiction was 21 volumes in October, and the maximum value for non-fiction was 23 volumes in November. In other words, we can see that October and November are the times when people buy and read a lot of books, regardless of genre. On the contrary, the minimum value for fiction was 9 volumes, which was in December, and the minimum value for nonfiction was 4, which was in January and July. Through this, I learned that December and January are times when people do not read many books, regardless of genre. This trend was also found in the results of a monthly analysis of the proportion of newly added books by genre. The increase or decrease in fiction and non-fiction showed similar trends. In particular, the ratio of new books was highest in September, October, and November, while the ratio was found to drop sharply in December. In summary, the number of new books by genre began to increase in August and was highest in September, October, and November. In comparison, the volume of new publications decreased significantly in December and January. Publishers appear to have started publishing new books in advance, perhaps targeting the December and January markets when Christmas or New Year’s Day takes place. Just as Christmas season movies usually start showing two weeks before Christmas, it seems likely that books will tend to be published several months before the season begins.
As a result of calculating the correlation coefficient to analyze the correlation between fiction and nonfiction, 0.675 was calculated. The correlation coefficient has a value from -1 to 1. Considering that the closer it is to 1, the more positive the correlation is, and the closer it is to -1, the more negative the correlation is, fiction and non-fiction were analyzed to have a strong, positive correlation.
To analyze this relationship in more detail, regression analysis was performed. As a result of conducting a regression analysis with the nonfiction ratio as the dependent variable and the fiction ratio as the explanatory variable, the regression coefficient was estimated to be a positive number of 1.0458, indicating that fiction and nonfiction are positively correlated. Also, at this time, the R-square value was 0.483, showing that 48.3% of the non-fiction ratio could be explained by the fiction ratio.
