药食同源类阿里巴巴直播带货违法监测预警数据
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对采集的阿里巴巴平台带货品类为药食同源类的达人直播视频内容进行转译分析，对达人口播语言内容进行处理、分析，根据达人在直播过程中对预先设置的违规敏感词（比如：彻底根治、绝对安全、无任何副作用、快速见效、立竿见影、包治百病、100%纯天然、预防疾病、抗癌、抗衰老、政府推荐等）违反的次数和频率，依据触发条件规则提出警告或处理。为服务辖区市场监督局管理区域内规范企业阿里巴巴直播行为，提供数据支持。将采集完成的直播视频进行进行预处理，第一步：基于原始视频文件，以最大10分钟单位对原始视频进行切片。第二步：对于已完成的切片视频，进行视频内容转语音操作。第三步：对于已完成视频转语音操作的切片，进行语音转文本操作。第四步：使用OCR技术对原始视频中抓取的图片进行文字提取操作。第五步：将所得到的文字内容与违法预警关键词库进行匹配。最终运用多标准决策分析模型，对主播在直播过程中出现的违规语句进行分析计算，得出违法预警值和是否预警判断。违法预警值 ≤1 时，不触发预警提示，违法预警值 ＞1 时触发违法预警提示。
This dataset performs transcription and analysis on collected live streaming video content from influencers on the Alibaba platform, where the product category for their live streaming commerce is medicine-food homologous materials. The spoken language content of the influencers during live broadcasts is processed and analyzed, and warnings or penalties are issued in accordance with trigger condition rules based on the number and frequency of violations of pre-configured sensitive prohibited keywords (including: complete radical cure, absolutely safe, no side effects whatsoever, rapid effect, immediate effect, cure all diseases, 100% pure natural, disease prevention, anti-cancer, anti-aging, government recommendation, etc.). This work provides data support for market supervision bureaus in their respective jurisdictions to regulate the live streaming behaviors of enterprises on the Alibaba platform. The collected live streaming videos undergo preprocessing through the following steps: Step 1: Slice the original video files into segments with a maximum duration of 10 minutes per segment. Step 2: Convert the content of the sliced videos into speech via video-to-speech conversion. Step 3: Convert the speech obtained from the video-to-speech conversion into text via speech-to-text technology. Step 4: Extract text from images captured from the original videos using OCR technology. Step 5: Match the obtained text content against the violation warning keyword database. Finally, a multi-criteria decision analysis model is employed to analyze and calculate the violation statements made by the anchors during live streaming, thereby deriving the violation warning value and making a corresponding warning judgment. No warning prompt will be triggered if the violation warning value is ≤ 1, while a violation warning prompt will be triggered if the violation warning value is > 1.
