Skip to main content

Sentiment analysis for paragraph or sentence

Project description

sentiment_analysis (감성 분석)

일기 및 일상 평문 텍스트에서, 글쓴이의 감정을 유추하기 위해서 만들어진 라이브러리입니다. 감성 분석을 위해서, Keras 및 nltk가 사용되었습니다. 또한, 텍스트의 길이에 따라서 문장을 요약하고 이에 대한 감성을 각각 분석을 하기 위해 Lexrank 알고리즘이 사용되었습니다.

Installation

pip install sentiment-analysis

Usage

from sentiment_analysis import

Reference)

  1. https://github.com/theeluwin/lexrankr (Korean Lexrank)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

sentiment_analysis-0.0.2-py3-none-any.whl (2.5 kB view details)

Uploaded Python 3

File details

Details for the file sentiment_analysis-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: sentiment_analysis-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 2.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for sentiment_analysis-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 5ae3688cfe76166a8f51fa28a2031f7391a8d9edfe1255c35013c07878f40622
MD5 63f48f36bc34185469af126e24ffbaf3
BLAKE2b-256 21572b4ca1fbb6ae6efeea0c812c01dfa236646406d72392a6dccb19641752ec

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page