Quickstart

Here’s a quickstart guide, explaining how to use pyliwc perform text analysis.

Liwc is the main class for interacting with the LIWC CLI.

liwc = Liwc(liwc_cli_path='LIWC-22-cli', threads=None, verbose=True)

Parameters: - liwc_cli_path (str): Path to the LIWC CLI executable. Default is ‘LIWC-22-cli’. On WSL, it is required to add .exe at the end ‘LIWC-22-cli.exe’, - threads (int, optional): Number of threads to use. Defaults to the number of CPU cores minus one. - verbose (bool, optional): If True, display printing such as progress bar for large files. Defaults to False.

The main Class of Pyliwc is Liwc.

Note: Make sure that you have LIWC-22 software running on your computer — it is required for using all methods

Analyze a string using the default dictionary (LIWC22)

from pyliwc import Liwc

liwc = Liwc('LIWC-22-cli.exe')

text = "This is a sample text for LIWC analysis."

r = liwc.analyze_string_to_json(text)

Picked up JAVA_TOOL_OPTIONS: -Dfile.encoding=UTF-8

{
    'Segment': 1,
    'WC': 8,
    'Analytic': 89.52,
    'Clout': 40.06,
    'Authentic': 15.38,
    'Tone': 20.23,
    'WPS': 8,
    'BigWords': 12.5,
    'Dic': 100,
    'Linguistic': 62.5,
    'function': 50,
    'pronoun': 12.5,
    'ppron': 0,
    'i': 0,
    'we': 0,
    'you': 0,
    ... ,
    'AllPunc': 12.5,
    'Period': 12.5,
    'Comma': 0,
    'QMark': 0,
    'Exclam': 0,
    'Apostro': 0,
    'OtherP': 0,
    'Emoji': 0
}

Analyzing Texts from a pandas DataFrame

import pandas as pd
df = pd.read_csv('../data/US-president.csv')

from pyliwc import Liwc

liwc = Liwc('LIWC-22-cli.exe')

liwc.analyze_df(df.Text, liwc_dict="LIWC22")

	Segment	WC	Analytic	Clout	Authentic	Tone	WPS	BigWords	Dic	Linguistic	...	nonflu	filler	AllPunc	Period	Comma	QMark	Exclam	Apostro	OtherP	Emoji
Row ID
0	1	1592	52.22	93.17	34.71	79.12	16.58	22.49	91.21	66.46	...	0	0	14.20	5.97	6.53	0.06	0	0.63	1.01	0
1	1	2389	51.22	95.37	36.07	54.01	20.25	19.21	90.37	68.48	...	0	0	12.98	5.11	6.20	0.00	0	0.54	1.13	0
2	1	1457	46.94	98.19	42.58	82.46	16.19	21.89	91.08	66.78	...	0	0	15.31	6.18	7.28	0.00	0	0.75	1.10	0
3	1	2548	43.37	91.33	50.66	45.63	15.35	17.39	93.21	71.15	...	0	0	19.66	6.28	9.11	0.39	0	1.69	2.20	0

4 rows × 119 columns

Change to other dictionary: “LIWC2015”

liwc_dict = "LIWC2015" 

liwc.analyze_df(df.Text, liwc_dict=liwc_dict)

	Segment	WC	Analytic	Clout	Authentic	Tone	WPS	Sixltr	Dic	function	...	Colon	SemiC	QMark	Exclam	Dash	Quote	Apostro	Parenth	OtherP	Emoji
Row ID
0	1	1592	65.12	92.38	30.27	89.13	16.58	22.49	89.38	53.33	...	0.38	0.38	0.06	0	0.00	0.25	0.63	0	0.00	0
1	1	2389	64.97	93.13	33.34	74.15	20.25	19.21	87.57	55.04	...	0.13	0.21	0.00	0	0.63	0.08	0.54	0	0.08	0
2	1	1457	57.63	96.73	40.07	87.87	16.19	21.89	87.99	53.12	...	0.55	0.34	0.00	0	0.07	0.14	0.75	0	0.00	0
3	1	2548	58.30	91.76	44.26	62.24	15.35	17.39	90.07	55.42	...	0.90	0.39	0.39	0	0.16	0.63	1.69	0	0.12	0

4 rows × 95 columns

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