电动自行车类抖音直播带货违法监测预警数据

对采集的抖音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抖音直播行为，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 dataset focuses on the transcription and analysis of live stream video content from Douyin influencers who promote electric bicycle products. We process and analyze the spoken content delivered by influencers during their live broadcasts. Based on the frequency and count of violations of pre-configured sensitive prohibited words (such as "mutual recognition agreement", "speed limit removal", "battery capacity", "removable battery", "200km cruising range", "elevator-accessible", "replaceable battery", "ultra-high-power motor", etc.) by the influencers, warnings or corresponding penalties will be issued in accordance with the trigger rules. This work provides data support for standardizing the live streaming behaviors of enterprises on Douyin within the jurisdiction of the Zhuji Municipal Market Supervision and Administration Bureau.

The preprocessing of the collected live stream videos is carried out in five steps:
1. Slice the original video files into segments with a maximum duration of 10 minutes each;
2. Perform video-to-speech conversion on the sliced videos;
3. Conduct speech-to-text conversion on the speech content extracted from the sliced videos;
4. Extract text from images captured in the original videos using OCR technology;
5. Match the obtained text content against the violation early warning keyword database.

Finally, a multi-criteria decision analysis (MCDA) model is utilized to analyze and calculate the violation statements made by the streamer during the live broadcast, so as to obtain the violation early warning score and the judgment of whether to trigger an early warning.

The violation early warning score is calculated via the following formula:
Violation Early 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 stream room in the past month * 0.1)

According to the calculation results, no early warning prompt will be triggered if the violation early warning score is ≤ 1, while a violation early warning prompt will be triggered if the score is > 1.

搜集汇总

数据集介绍

特点

该数据集用于监测抖音电动自行车直播中的违法行为，包含2180条记录，通过语音转文本和OCR技术匹配关键词计算违法预警值，每季度更新一次。