社交媒体舆情数据集合

核心采用“定向采集-情感分析-趋势预测”三阶联动算法架构，细节如下：①定向采集算法：运用关键词精准匹配爬虫算法，聚焦“贵州酱酒”“茅台镇酱酒”等核心词实现数据定向抓取，采集精准度≥97%；②情感分析算法：基于RoBERTa预训练模型，结合酱酒行业语料库优化模型，对舆情文本进行情感标注，情感识别准确率≥94%；③趋势预测算法：以48小时为周期，构建酱酒舆情热度-时间的GRU神经网络模型，预判舆情发展趋势。算法经2亿+条酱酒相关文本训练，经第三方机构验证：舆情预警响应时间≤30秒，酱酒热点话题识别准确率≥96%，每月基于500万+条新增数据增量训练。

The core framework adopts a three-stage linked algorithm architecture of "targeted data collection - sentiment analysis - trend prediction", with detailed components as follows: ① Targeted data collection algorithm: A keyword-precision matching crawler algorithm is applied, focusing on core keywords such as "Guizhou sauce-flavored liquor" and "sauce-flavored liquor from Maotai Town" to achieve targeted data crawling, with a collection accuracy of ≥97%; ② Sentiment analysis algorithm: Based on the RoBERTa pre-trained model, combined with the sauce-flavored liquor industry corpus for model optimization, sentiment annotation is performed on public opinion texts, with a sentiment recognition accuracy of ≥94%; ③ Trend prediction algorithm: Taking a 48-hour cycle as the time frame, a GRU neural network model of sauce-flavored liquor public opinion heat versus time is constructed to predict the development trend of public opinion. The algorithm has been trained on over 200 million pieces of sauce-flavored liquor-related texts. Verified by a third-party institution, the public opinion early warning response time is ≤30 seconds, the recognition accuracy of sauce-flavored liquor hot topics reaches ≥96%, and incremental training is conducted monthly based on more than 5 million newly added data entries.

搜集汇总

背景与挑战

背景概述

该数据集是一个针对酱酒行业的社交媒体舆情数据集合，由贵州酱酒集团有限公司自行产生，规模为10G，每周更新。它主要用于品牌舆情监测、产品口碑分析和市场趋势预测，采用定向采集、情感分析和趋势预测算法，具有高准确率和快速响应特点，服务于酱酒生产企业、品牌运营机构等行业相关方。