File: repl.txt

package info (click to toggle)
node-stdlib 0.0.96%2Bds1%2B~cs0.0.429-2
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 421,476 kB
  • sloc: javascript: 1,562,831; ansic: 109,702; lisp: 49,823; cpp: 27,224; python: 7,871; sh: 6,807; makefile: 6,089; fortran: 3,102; awk: 387
file content (43 lines) | stat: -rw-r--r-- 1,486 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43

{{alias}}()
    Returns a list of English words rated for valence.

    The returned list contains 2477 English words (and phrases) rated for
    valence. Negative words have a negative valence [-5,0). Positive words have
    a positive valence (0,5]. Neutral words have a valence of 0.

    A few notes:

    - The list includes misspelled words. Their presence is intentional, as such
      misspellings frequently occur in social media content.
    - All words are lowercase.
    - Words may contain numbers; e.g., "n00b".
    - Some "words" are phrases; e.g., "cool stuff", "not good".
    - Words may contain apostrophes; e.g., "can't stand".
    - Words may contain diaeresis; e.g., "naïve".
    - Words may contain dashes; e.g., "self-deluded", "self-confident".

    Returns
    -------
    out: Array<Array>
        List of English words and their valence.

    Examples
    --------
    > var list = {{alias}}()
    [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]

    References
    ----------
    - Nielsen, Finn Årup. 2011. "A new ANEW: Evaluation of a word list for
    sentiment analysis in microblogs." In *Proceedings of the ESWC2011 Workshop
    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,
    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.
    pdf>.

    * If you use the list for publication or third party consumption, please
    cite the listed reference.

    See Also
    --------