电动自行车类淘宝直播带货违法监测预警数据

对采集的淘宝平台带货品类为电动自行车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：能互认协议，解限速，曾容量，可拆卸电池，续航里程200公里，可进电梯，可换电池，超强大电机等）违反的次数和频率，依据触发条件规则提出警告或处理。为诸暨市市场监督局管理区域内规范企业淘宝直播行为，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=（违法预警单关键词命中次数*0.25）+（违法预警组合关键词命中次数* 0.3）+（图片识别命中预警组合关键词个数*0.35）+（直播间近一个月历史违规记录数*0.1） 通过公式计算出最终违法预警值，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 work performs transcription and analysis on collected live streaming videos of influencers promoting electric bicycle products on the Taobao platform, and processes and analyzes the spoken language content of the influencers. Based on the frequency and times of violations of pre-set sensitive violation keywords (such as mutual recognition agreement, speed limit unlocking, battery capacity, detachable battery, 200-kilometer cruising range, elevator-accessible, replaceable battery, ultra-powerful motor, etc.) during the live broadcast, warnings or penalties will be issued according to the trigger condition rules. This work provides data support for standardizing the Taobao live streaming behaviors of enterprises within the regulatory jurisdiction of the Zhuji Municipal Market Supervision Administration. The collected live streaming videos undergo the following preprocessing steps: Step 1: Slice the original video files into segments with a maximum duration of 10 minutes. Step 2: Convert the sliced videos into audio tracks. Step 3: Convert the audio tracks from the processed sliced videos into text. Step 4: Extract text from images captured in the original videos using OCR technology. Step 5: Match the extracted text content against the violation warning keyword database. Finally, a multi-criteria decision analysis model is applied to analyze and calculate the violation statements made by the streamer during the live broadcast, to derive the violation warning score and the warning judgment result. The violation warning score is calculated via the following formula: Violation Warning Score = (Number of hits for single violation warning keywords * 0.25) + (Number of hits for combined violation warning keywords * 0.3) + (Number of combined warning keywords identified via image recognition * 0.35) + (Number of historical violation records of the live broadcast room in the past month * 0.1) The final violation warning score is calculated using the above formula. No warning prompt will be triggered when the score ≤ 1, and a violation warning prompt will be triggered when the score > 1.