基于校园社交网络数据的情绪分析及可视化

Emotional Analysis and Visualization Based on Campus Social Network Data

以社交网络中活跃的大学生用户群的QQ空间、说说等文本数据为对象,依据四类基础词库(积极、消极、否定词、程度词),结合Python第三方库Pandas库和matplotlib库,给出了5-LevelEA情绪分析算法。该算法能计算出社交网络文本数据中的多项情绪指标,再通过可视化图表呈现所采集数据中的个人情绪变化趋势以及性别、就业情况等要素作用下的情绪分类数据,具有实用价值。

Based on the QQ space, speaking text data of the active college student user groups in the social network, according to thefour basic lexicons(positive, negative, negative, degree words), combined with the Python third-party library Pandas library andmatplotlib library, A 5-levelEA emotional analysis algorithm is given. The algorithm can calculate a number of emotional indica-tors in the social network text data, and display the emotional classification trends in the collected data and the emotional classifica-tion data under the influence of gender and employment conditions through the visualization chart.The test data shows that the algo-rithm has certain effectiveness.