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詞典的輸出與試用版的不同

[英]Dictionary different output than the trial site version

我嘗試在R中使用LIWC字典2015​​版。

用於文本分析的虛擬文本:

Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis, sem. Nulla consequat massa quis enim. Donec pede justo, fringilla vel, aliquet nec, vulputate eget, arcu. In enim justo, rhoncus ut, imperdiet a, venenatis vitae, justo. Nullam dictum felis eu pede mollis pretium. Integer tincidunt. Cras dapibus. Vivamus elementum semper nisi. Aenean vulputate eleifend tellus. Aenean leo ligula, porttitor eu, consequat vitae, eleifend ac, enim. Aliquam lorem ante, dapibus in, viverra quis, feugiat a, tellus. Phasellus viverra nulla ut metus varius laoreet. Quisque rutrum. Aenean imperdiet. Etiam ultricies nisi vel augue. Curabitur ullamcorper ultricies nisi. Nam eget dui. Etiam rhoncus. Maecenas tempus, tellus eget condimentum rhoncus, sem quam semper libero, sit amet adipiscing sem neque sed ipsum. Nam quam nunc, blandit vel, luctus pulvinar, hendrerit id, lorem. Maecenas nec odio et ante tincidunt tempus. Donec vitae sapien ut libero venenatis faucibus. Nullam quis ante. Etiam sit amet orci eget eros faucibus tincidunt. Duis leo. Sed fringilla mauris sit amet nibh. Donec sodales sagittis magna. Sed consequat, leo eget bibendum sodales, augue velit cursus nunc

我嘗試以下行:

library("LIWCalike")
library("quanteda")
 liwcalike(data_char_testphrases)
liwc2015dict <- dictionary(file = "~/Dropbox/QUANTESS/dictionaries/LIWC/LIWC2015_English_Flat.dic",
'                            format = "LIWC")
' inaugLIWCanalysis <- liwcalike(data_corpus_inaugural, liwc2015dict)
' inaugLIWCanalysis[1:6, 1:10]

我希望可以得到以下類似結果,這些結果可以在官方站點上復制出來,作為簡單示例,當然,我相信LIWC會有更多變量,這些是一些示例

LIWC Dimension  Your
Data    Personal
Texts   Formal
Texts
Self-references (I, me, my) 5.18    11.4    4.2
Social words    2.59    9.5 8.0
Positive emotions   2.35    2.7 2.6
Negative emotions   1.18    2.6 1.6
Overall cognitive words 6.59    7.8 5.4
Articles (a, an, the)   8.71    5.0 7.2
Big words (> 6 letters) 20.24   13.1    19.6

但是我收到以下結果:

output[, c(1:7, ncol(output)-2)]
#>    docname Segment WC WPS Sixltr   Dic LINGUISTIC PROCESSES.FUNCTION WORDS
#> 1    text1       1  8   3  37.50 37.50                               25.00
#> 2    text2       2  6   5  16.67 50.00                               50.00
#> 3    text3       3  4   2   0.00 25.00                                0.00
#> 4    text4       4 18  12  11.11 61.11                               22.22
#> 5    text5       5  4   1   0.00 25.00                                0.00
#> 6    text6       6  7   3  14.29 28.57                               14.29
#> 7    text7       7  7   3   0.00 42.86                               28.57
#> 8    text8       8  5   4   0.00 80.00                               60.00
#> 9    text9       9  9   2  11.11 11.11                               11.11
#> 10  text10      10  9   2  22.22 22.22                               22.22
#>    Apostro
#> 1        0
#> 2        0
#> 3        0
#> 4        0
#> 5        0
#> 6        0
#> 7        0
#> 8        0
#> 9        0
#> 10       0

如何在LIWC的示例試用版中獲取結果?

有關如何獲得與LIWC幾乎相同的結果,請參見此頁面: https ://koheiw.net/ ? p = 573

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