How to evaluate your publication?

New Year is coming. In Khabarovsk, he has already arrived, congratulations!

By tradition, you need to take stock of the outgoing year, and I decided to re-read my posts. Reread something re-read, but how to evaluate them? Karma? Rating? Views? Too dry and serious. The parrots? Too frivolous. I decided to measure in Milfgard.


Measurement technique: we get posts Milfgard , and we consider the frequency of use of letters. The simplest analogue of phonosemantic analysis.

public static class SymbolsExtractor { private static readonly char[] _russianSymbols = "".ToCharArray(); // 33   public static char[] RussianSymbols => _russianSymbols.ToArray(); public static Dictionary<char, double> SymbolsFrequences(this string text) { var symbolsQty = text.ToCharArray().Count(symbol => _russianSymbols.Contains(symbol)); //   (   ) double symbolPercentage = 1.00/symbolsQty; var result = new Dictionary<char, double>(); foreach (char russianSymbol in _russianSymbols) { double inclusions = text.ToLower().ToCharArray() .Count(textSymbol => textSymbol == russianSymbol) //        * (symbolPercentage); //     inclusions = Math.Round(inclusions, 3); //     result.Add(russianSymbol, inclusions); } return result; //  :     } } 

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I took the last five posts, the first five, and counted the medians. Result (Letter-Early Miefgard-Late Miefgard):

but	0.0864	0.09
b	0.0148	0.0172
at	0.043	0.0388
g	0.0164	0.0166
d	0.0294	0.0292
...
	0	0
s	0.0228	0.0204
s	0.0176	0.0186
uh	0.0038	0.0042
Yu	0.0064	0.0058
I	0.0186	0.018

As you can see, there is a difference. Obviously, it is necessary to compare with the latest posts, but I see 2016 off. It is necessary to compare quickly: in two hours at the table. Therefore, the standard deviation from the Millgard median does not roll. Instead, I additionally take the median from the Alizar posts, and compare my median with Malfgardova and Alizarova.

 int result = 0; foreach (var stat in stats) { double MilfgardDiff = Math.Abs(stat.NewMilfgard - stat.Oxoron); //  :   Milfgard double AlizarDiff = Math.Abs(stat.Alizar - stat.Oxoron); //  :   Alizar char res = MilfgardDiff > AlizarDiff ? 'M' : Math.Abs(MilfgardDiff - AlizarDiff) < 0.0001 ? 'N' : 'A'; if (res == 'M') result++; //   Milfgard if (res == 'A') result--; //   Alizar } Console.WriteLine(); Console.WriteLine(result < 0 ? $"{-result} ALizar" : $"{result} Milfgard"); // .   - 8 Alizar 

As you can see, the resulting evaluation method is simple and universal. The area of ​​its application is extremely wide: you can compare your similarity with javista and sharpista, rubistami and pkhpeshnikami, efsharpistami and kaskelististami. You can also determine which JS framework best suits your personality. But whatever the result is, go for new heights, colleagues, so that other people compare themselves with you. Happy holiday!

PS Milfgard and Alizar are selected solely to demonstrate the work of the method, as one of the most remarkable authors Habra.