utl_sentiment_analysis

Was the antidepressant effective. Psychometric measurement of skills and knowledge, abilities, attitudes, personality traits, and educational achievement. Measurement of well being. Keywords: sas sql join merge big data analytics macros oracle teradata mysql sas communities stackoverflow statistics artificial inteligence AI Python R Java Javascript WPS Matlab SPSS Scala Perl C C# Excel MS Access JSON graphics maps NLP natural language processing.

语言SAS
默认分支master
大小4 KB
更新2018年10月8日

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rogerjdeangelis

项目介绍

rogerjdeangelis/utl_sentiment_analysis 是一个托管在 GitHub 上的开源项目，主要使用 SAS 编写，采用 MIT License 许可证，目前获得 2 个 Star、0 次 Fork。

仓库全名: rogerjdeangelis/utl_sentiment_analysis

README 摘要

utlsentimentanalysis Was the antidepressant effective SAS Forum: Pulling themes from a qualitative variable (sentiment analysis) WPS/SAS/R Innovation: AI: Was the antidepressant effective. WORKING CODE Was the antidepressant effective beforetreatment=c('I am lonely.', 'I lost.', 'I am tired.', 'I am crying.') aftertreatement=c('I love it.', 'I am happy.', 'Beautiful Day.', 'SAS, R and WPS are fun.')…

完整内容见 GitHub 原始 README 或本页。

常见问题

utl_sentiment_analysis 用什么语言开发？

主要使用 SAS 编写，采用 MIT License 许可证，目前有 2 个 Star。

utl_sentiment_analysis 可以免费商用吗？

仓库采用 MIT License 许可证，可免费使用与修改，商业使用请遵守许可证条款（例如保留版权声明与许可声明）。

如何获取 utl_sentiment_analysis 的源码？

可以直接克隆仓库：git clone https://github.com/rogerjdeangelis/utl_sentiment_analysis.git，默认分支为 master；安装与运行步骤见仓库 README。

utl_sentiment_analysis 最近还在维护吗？

仓库最近一次更新为 2018年10月8日，当前没有未关闭的 Issue；Star 数为 2，可作为社区活跃度的参考。

关于

MIT License
2 Stars
0 Forks
1 Watching

简要分析

热度分

3

价值分

1

活跃状态

活跃

语言占比

SAS

贡献者

rogerjdeangelis

rogerjdeangelis

utl_sentiment_analysis

Was the antidepressant effective

 SAS Forum: Pulling themes from a qualitative variable (sentiment analysis)

 WPS/SAS/R Innovation: AI: Was the antidepressant effective.


    WORKING CODE

        Was the antidepressant effective

         before_treatment=c('I am lonely.', 'I lost.', 'I am tired.', 'I am crying.')
         after_treatement=c('I love it.', 'I am happy.', 'Beautiful Day.', 'SAS, R and WPS are fun.')

         sentiment<-syuzhet::get_nrc_sentiment(syuzhet::get_sentences(before_treatment));
         sentiment<-cbind(time=c('&time'),sentence=c(1:4),sentiment);


         sentiment<-syuzhet::get_nrc_sentiment(syuzhet::get_sentences(after_treatement));
         sentiment<-cbind(time=c('&time'),sentence=c(1:4),sentiment);


 WPS/SAS/R Innovation: AI: Was the treatment effective?

 HAVE   These sentiments
 =======================

   Today

         I am lonely.
         I lost.
         I am tired.
         I am crying.

    Tomorrow

         I love it.
         I am happy.
         Beautiful Day.
         SAS, R and WPS are fun.



 WANT to know if the outlook is good (think stock market)
 =========================================================

 Looks like things are looking up

 Today has 100% negative sentiments

 TIME     POSITIVE    NEGATIVE    Frequency     Percent
 -------------------------------------------------------
 today           0           1           4      100.00      100% negative

 Tomorrow has 100% positive sentiments


 TIME        POSITIVE    NEGATIVE    Frequency     Percent
 ----------------------------------------------------------
 tomorrow           1           0           4      100.00   100 percent positive

 Detail

 Up to 40 obs WORK.TIME total obs=8

 Obs    TIME        SENTENCE    ANGER    ANTICIPATION    DISGUST    FEAR    JOY    SADNESS    SURPRISE    TRUST

  1     today           1         1            0            1         1      0        1           0         0
  2     today           2         0            0            0         0      0        1           0         0
  3     today           3         0            0            0         0      0        0           0         0
  4     today           4         0            0            0         0      0        1           0         0

  5     tomorrow        1         0            0            0         0      1        0           0         0
  6     tomorrow        2         0            1            0         0      1        0           0         1
  7     tomorrow        3         0            0            0         0      1        0           0         0
  8     tomorrow        4         0            1            0         0      1        0           0         0


 Up to 40 obs WORK.TIME total obs=8

 Obs    TIME        SENTENCE   NEGATIVE    POSITIVE

  1     today           1          1           0
  2     today           2          1           0
  3     today           3          1           0
  4     today           4          1           0

  5     tomorrow        1          0           1
  6     tomorrow        2          0           1
  7     tomorrow        3          0           1
  8     tomorrow        4          0           1

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