Twitter上药物分析的数据挖掘策略

Kartik Sharma, Deepak Kumar, S. Khatri, S. Som
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引用次数: 0

摘要

这项研究发现并分析了twitter上各种与毒品(杂草)相关的推文。在这方面,我们在2018年10月的研究中收集了5000条与药物相关的推文。我们对文本算法和数据分析的研究揭示了一些有趣的模型,这些模型加入了用户的态度,这将通过twitter中外部链接的存在来区分。从最近的调查中可以看出,72%的人使用智能手机上传文本,而其他用户则通过电脑等操作;与工作日相比,人们通常在周六和周日发推文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Mining Strategies for Drug Analysis on Twitter
This research discovers and analyses various drugs (weed) associated tweets on twitter. In this regard, we have gathered 5000 drugs associated tweets throughout October 2018 in our research study. Our study related to texting top of algorithms and data analysis reveal some interesting models that add in users' attitude which would be distinguished by the subsistence of outer link in tweet. From the recent survey, it is evident that 72% people upload their text using their smart phones while other users operate via computers etc; people usually tweet on Saturday and Sunday in large number when compared with the weekdays.
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