/// <summary>
/// Calculates Inclusion Value
/// </summary>
/// <returns>
/// Returns value from -1 to 1
/// </returns>
public static double CalculateInclusion(EmotionState info, double incl, double excl, double syntax_value)
{
double result = 0;
if (incl + excl == 0)
{
//if there is no familiar inclusivity words in sentence
//we should export some value from emotions and sentiment value to not export zero result
if (info.Sentiment > 0)
{
result = 0.1 * info.Sentiment + syntax_value;
}
else
{
result = 0.1 * info.Sentiment - syntax_value;
}
return(result);
}
if (incl >= excl)
{
result = CustomPowerfunction(0.9, (incl - excl + 1)) + syntax_value;
return(result);
}
else
{
result = CustomPowerfunction(0.9, (excl - incl + 1)) + syntax_value;
return(-result);
}
}
/// <summary>
/// Analyses <see cref="text"/> data
/// </summary>
/// <param name="text">
/// actual text which should be analyzed
/// </param>
/// <returns>
/// The <see cref="EmotionState"/> type variable is the result of this analyze
/// which stores all the values being analyzed
/// </returns>
public EmotionState DoAnalysis(string text)
{
//count speech parts
string[] tokens = Library.tokenizer.Tokenize(text); //divide sentence into words
for (int j = 1; j < tokens.Count(); j++)
{
if (tokens[j - 1] == ":" && tokens[j].Length <= 3)
{
tokens[j] = ":" + tokens[j];
}
}
string[] tags = Library.posTagger.Tag(tokens); //and also get for each word what speech part it is
EmotionState result = AnalyseSentence(tokens, tags); //merge each result for each sentence to get final result
return(result);
}
/// <summary>
/// Calculates Emotion Values
/// </summary>
/// <returns>
/// Fills values of emotion types in info variable.
/// Values are from 0 to 1.
/// </returns>
public static EmotionState CalculateEmotions(EmotionState info, double syntax_value)
{
//about joy
// 30% sentiment value, 60% already collected info.joy , 10% syntax value
info.Joy = Math.Max(syntax_value, 0.3 * info.Sentiment + CustomPowerfunction(0.6, info.Joy) + syntax_value);
//about sadnass
// 40% sentiment value, 50% already collected info.joy , 10% syntax value
info.Sadness = Math.Max(syntax_value, -0.4 * info.Sentiment + CustomPowerfunction(0.5, info.Joy) + syntax_value);
//about disgust
// 25% sentiment value, 65% already collected info.joy , 10% syntax value
info.Disgust = Math.Max(syntax_value, -0.25 * info.Sentiment + CustomPowerfunction(0.65, info.Joy) + syntax_value);
//about fear
// 20% sentiment value, 70% already collected info.joy , 10% syntax value
info.Fear = Math.Max(syntax_value, -0.20 * info.Sentiment + CustomPowerfunction(0.50, info.Joy) + syntax_value);
//about anger
// 30% sentiment value, 60% already collected info.joy , 10% syntax value
info.Anger = Math.Max(syntax_value, -0.30 * info.Sentiment + CustomPowerfunction(0.60, info.Joy) + syntax_value);
return(info);
}
/// <summary>
/// Calculates Sentiment Values
/// </summary>
/// <returns>
/// Value from -1 to 1
/// </returns>
public static double CalculateSentiment(EmotionState info, double pos, double neg, double incl, double excl, double syntax_value)
{
if (pos == 0 && neg == 0 && incl == 0 && excl == 0 && info.Joy + info.Fear + info.Disgust + info.Sadness + info.Anger == 0)
{
//this means absolutily nothing is familiar in text,then
//we are calculating sentiment syntax
info.Sentiment = syntax_value;
return(info.Sentiment);
}
double result = 0;
if (pos >= neg) //if positive is greater then negative,it includes emotions and inclusivity
{
//this means sentiment is positive,
result = CustomPowerfunction(0.9, (pos - neg + 1)) + syntax_value;
return(result);
}
else
{
result = CustomPowerfunction(0.9, (neg - pos + 1)) + syntax_value;
return(-result);
//so if it comes here it means sentiment is negative
}
}
/// <summary>
/// Analyze each tokens with speech parts
/// </summary>
private EmotionState AnalyseSentence(string[] words, string[] parts)
{
EmotionState Result = new EmotionState(); //calc is the total emotion and sentiment values of each words
//here we are collecting info from emotion data
foreach (string word in words)
{
double coeff = word == HelperMethods.ToLowRegistry(word) ? 1 : high_capital_factor;
int[] values = null;
if (Library.IsEmotionsAvaliable(word))
{
values = Library.GetEmotions(word);
}
if (values != null)
{
//increase values of each thing
Result.Anger += values[0] * coeff;
Result.Disgust += values[1] * coeff;
Result.Fear += values[2] * coeff;
Result.Joy += values[3] * coeff;
Result.Sadness += values[4] * coeff;
}
}
double incl_val = 0, excl_val = 0;
foreach (string word in words)
{
double coeff = word == HelperMethods.ToLowRegistry(word) ? 1 : high_capital_factor;
if (Library.GetInclusionValue(word) > 0)
{
incl_val += 1 * coeff;
}
if (Library.GetExclusionValue(word) > 0)
{
excl_val += 1 * coeff;
}
}
double pos_val = Result.Joy + incl_val;
double neg_val = excl_val + Result.Disgust + Result.Sadness + Result.Fear + Result.Anger;
//lets translate emotions into positive and negative values, only joy is positive others are negative
//here we are collecting results from positive and negative data
foreach (string word in words)
{
double coeff = word == HelperMethods.ToLowRegistry(word) ? 1 : high_capital_factor;
if (Library.IsPositive(word))
{
pos_val += 1 * coeff;
}
if (Library.IsNegative(word))
{
neg_val += 1 * coeff;
}
}
//now we have collected anger,fear,sadness,joy,disgust pos_val,neg_val incl_val,excl_val
//before summarise we have to calculate syntax value
double syntax_value = MathAnalyzer.SyntaxValue(parts); //syntax value is a little point here
//but improtant its range is from 0 to 0.1
Result.Sentiment = MathAnalyzer.CalculateSentiment(Result, pos_val, neg_val, incl_val, excl_val, syntax_value); //calculating sentiment
Result = MathAnalyzer.CalculateEmotions(Result, syntax_value); //calculating emotions
//it is improtant that before running you already have calculatid sentiment
Result.Inclusion = MathAnalyzer.CalculateInclusion(Result, incl_val, excl_val, syntax_value);
//rounding values
Result.Sentiment = Math.Round(Result.Sentiment, 2);
Result.Fear = Math.Round(Result.Fear, 2);
Result.Disgust = Math.Round(Result.Disgust, 2);
Result.Anger = Math.Round(Result.Anger, 2);
Result.Sadness = Math.Round(Result.Sadness, 2);
Result.Joy = Math.Round(Result.Joy, 2);
Result.Inclusion = Math.Round(Result.Inclusion, 2);
//return result
return(Result);
}