Description Usage Arguments Value Note Source References See Also Examples

This routine creates a new object of type `SentimentDictionaryWeighted`

that
contains a number of words, each linked to a continuous score (i.e. weight) for
specifying its polarity. The scores can later be interpreted as a linear model

1 2 3 4 5 6 | ```
SentimentDictionaryWeighted(
words,
scores,
idf = rep(1, length(words)),
intercept = 0
)
``` |

`words` |
is collection (vector) of different words as strings |

`scores` |
are the corresponding scores or weights denoting the word's polarity |

`idf` |
provide further details on the frequency of words in the corpus as an additional source for normalization |

`intercept` |
is an optional parameter for shifting the zero level (default: 0) |

Returns a new object of type `SentimentDictionaryWordlist`

The intercept is useful when the mean or median of a response variable is not exactly located at zero. For instance, stock market returns have slight positive bias.

doi: 10.1371/journal.pone.0209323

Pr\"ollochs and Feuerriegel (2018). Statistical inferences for Polarity Identification in Natural Language, PloS One 13(12).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
# generate dictionary (based on linear model)
d <- SentimentDictionaryWeighted(c("increase", "decrease", "exit"),
c(+1, -1, -10),
rep(NA, 3))
summary(d)
# alternative call
d <- SentimentDictionaryWeighted(c("increase", "decrease", "exit"),
c(+1, -1, -10))
summary(d)
# alternative call
d <- SentimentDictionary(c("increase", "decrease", "exit"),
c(+1, -1, -10),
rep(NA, 3))
summary(d)
``` |

```
Attaching package: 'SentimentAnalysis'
The following object is masked from 'package:base':
write
Dictionary type: weighted (words with individual scores)
Total entries: 3
Positive entries: 1 (33.33%)
Negative entries: 2 (66.67%)
Neutral entries: 0 (0%)
Details
Average score: -3.333333
Median: -1
Min: -10
Max: 1
Standard deviation: 5.859465
Skewness: -0.6155602
Dictionary type: weighted (words with individual scores)
Total entries: 3
Positive entries: 1 (33.33%)
Negative entries: 2 (66.67%)
Neutral entries: 0 (0%)
Details
Average score: -3.333333
Median: -1
Min: -10
Max: 1
Standard deviation: 5.859465
Skewness: -0.6155602
Dictionary type: weighted (words with individual scores)
Total entries: 3
Positive entries: 1 (33.33%)
Negative entries: 2 (66.67%)
Neutral entries: 0 (0%)
Details
Average score: -3.333333
Median: -1
Min: -10
Max: 1
Standard deviation: 5.859465
Skewness: -0.6155602
```

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