## 3 Experimental Results  
As stated in previous lines, the Hurst parameter is applied to determine whether it is suitable to capture _linguistic structures_ within a text.  
The first result we provide is the existence of linguistic patterns in the scientific article regarding the confirmation of gravitational waves [4]. By inspecting such article it can be noticed that the following linguistic structures appear in the title and abstract:  
* Observation of gravitational waves from a binary black hole merger
* Gravitational-wave observatory
* observed
* gravitational-wave
* merger
* black-holes
* black hole
* gravitational waves
* observations
* binary
* black hole
* gravitational waves
* binary black hole merger  
Interestingly, such structures also appear along the body on the text, in different time instants. Figure 1 is the resultant time series of the scientific description regarding the confirmation of gravitational waves [4]. Its resultant Hurst exponent value is 0.677, which places the article in the category of persistent phenomena. It also indicates that the text is self-similar.  
The values of the Hurst parameter for the entire corpus are presented through box-plots and the cumulative probability function (**cpf**). According to [34], box plots provide information about the variability or dispersion of data. They are a standardized way of displaying the distribution of data based on:  
1. first quartile (Q1), corresponding to the 25 th percentile.
2. third quartile (Q3), corresponding to the 75 th percentile.
3. inter-quartile range (IQR): 25 th to 75 th percentile. That is to say, 50% of the data is contained in this range.
4. median.
5. minimum: Q1 - 1.5 IQR.
6. maximum: Q3 + 1.5 IQR.
7. Values below _minimum_ and above _maximum_ are outliers.  
Figure 2 shows the values for Hurst parameter.  
From the data presented in Figure 2, the median values of the Hurst exponent are:  
* 0.54 for business news.  
Figure 1: Resultant time series of the text that appear in [4] after it is mapped into ASCII code.  
* 0.49 for diffusion of science.
* 0.53 for entertainment news.
* 0.48 for random texts.
* 0.57 for scientific texts.  
It can also be observed that fifty percent of the Hurst parameter values for each category are placed in the following inter-quartile ranges (IQR's):  
* \((0.52,0.57]\) for business news.
* \([0.47,0.52]\) for diffusion of science.
* \([0.48,0.57]\) for entertainment news.
* \([0.48,0.5]\) for random texts.
* \([0.53,0.6)\) for scientific texts.  
Data within IQR represents \((+/-)0.6745\sigma\), where \(\sigma\) is one standard deviation. According to their distribution, data in scientific articles and randomly-generated texts are symmetrical. Randomly-generated texts present the least variability. Also, it is worth noticing that 75% of the Hurst parameter values for scientific texts are equal or greater than 0.53.  
The _cumulative probability functions_ that fit the Hurst parameter values are depicted in Figure 3.  
Figure 3: Cumulative Probability Functions of the Hurst parameter values.  
Figure 2: Box plots comparison of the Hurst parameter. From left to right: business, diffusion of science, entertainment, random and scientific texts.