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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (12): 52-59    DOI: 10.11925/infotech.2096-3467.2018.0415
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Identifying Trending Topics in Q&A Community with CART Decision Tree
Cheng Xiufeng1, Zhang Xinyi2, Wang Ning2()
1Institute of Scientific and Technical Information of China, Beijing 100038, China
2School of Information Management, Central China Normal University, Wuhan 430079, China
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Abstract  

[Objective] This paper tries to identify the trending topics, aiming to help the decision-making agencies manage online public opinion. [Methods] Firstly, we proposed the criteria to detect the trending topics of Q&A community. Then, we conducted an empirical study on China’s Zhihu Q&A community using the CART decision tree algorithm. [Results] The CART decision tree predicted the trending topics. [Limitations] We only collected data from a small portion of all topics on Zhihu. More data is needed for future studies. [Conclusions] The proposed method based on the CART decision tree algorithm could effectively predict trending topics in the Q&A community, which help us choose popular contents.
Key words： Decision Tree      Q&A Community      Trending Topics     
Received: 13 April 2018      Published: 16 January 2019
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Xiufeng Cheng
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Ning Wang

Cite this article:

Cheng Xiufeng,Zhang Xinyi,Wang Ning. Identifying Trending Topics in Q&A Community with CART Decision Tree. Data Analysis and Knowledge Discovery, 2018, 2(12): 52-59.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0415     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I12/52

特征 一级标准 二级标准
①吸引力较强 A问题关注度 A1浏览次数
②参与度较高 A2关注人数
③影响力较大 A3回答数量
④内容多样性 B问题内聚度 B1回答相近度
⑤间隔时间短 B2粒度特征值
⑥具备关键节点 C问题影响度 C1用户关键度
⑦传播速度快
Title Focus Cohesion Impact Is Order
Tree1.Topic1 1 379 560 8.99 502 643 1 25
Tree1.Topic2 9 495 9.81 83 591 1 49
Tree1.Topic3 356 204 8.04 522 595 1 55
Tree1.Topic4 51 740 8.23 89 478 1 63
Tree1.Topic5 347 185 9.28 994 162 1 93
Tree1.Topic6 3 496 1.98 8 874 1 94
Tree1.Topic7 8 538 3.64 597 1 96
Tree1.Topic8 4 361 4.41 10 818 1 99
Tree1.Topic9 56 159 3.33 93 735 1 110
Tree1.Topic10 35 877 1.82 21 288 1 115
Tree1.Topic11 6 600 5.86 5 318 1 118
Tree1.Topic12 403 128 8.66 97 756 1 121
Tree1.Topic13 4 249 1.89 1 108 1 124
Tree1.Topic14 703 195 15.20 52 308 1 128
Tree1.Topic15 1 327 4.31 2 760 1 136
Title Focus Cohesion Impact Is Order
Tree1.Topic16 109 452 15.91 109 622 0 137
Tree1.Topic17 95 0 0 0 139
Tree1.Topic18 648 7.18 457 0 145
Tree1.Topic19 5 068 3.49 111 0 149
Tree1.Topic20 950 3.27 11 670 0 153
Tree1.Topic21 801 1.53 46 0 159
Tree1.Topic22 1 472 1.97 44 0 163
Tree1.Topic23 791 2.37 586 0 164
Tree1.Topic24 426 1.83 12 650 0 173
Tree1.Topic25 281 1.85 68 0 180
Tree1.Topic26 871 3.39 5 181 0 203
Tree1.Topic27 1 196 2.11 144 588 0 207
Tree1.Topic28 576 3.13 9 949 0 209
Tree1.Topic29 408 1.95 16 350 0 213
Tree1.Topic30 463 2.46 465 0 234
Title Focus Cohesion Impact Is Order
Tree2.Topic1 109 452 15.91 109 622 1 1
Tree2.Topic2 403128 8.66 97 756 1 8
Tree2.Topic3 14 593 5.26 2 347 1 15
Tree2.Topic4 2 357 3.28 36 327 1 22
Tree2.Topic5 217 4.29 2 751 1 29
Tree2.Topic6 233 3.92 1 178 1 36
Tree2.Topic7 165 4.00 700 1 43
Tree2.Topic8 82 4.36 1 182 1 50
Tree2.Topic9 3 496 1.98 8 874 1 57
Tree2.Topic10 151 2.77 1 156 1 64
Tree2.Topic11 170 3.03 390 1 71
Tree2.Topic12 426 1.82 12 650 1 78
Tree2.Topic13 294 3.46 59 1 85
Tree2.Topic14 135 2.98 246 1 92
Tree2.Topic15 141 2.54 322 1 99
Title Focus Cohesion Impact Is Order
Tree2.Topic16 156 1.82 8 982 0 106
Tree2.Topic17 102 3.78 51 0 113
Tree2.Topic18 309 1.64 1 141 0 120
Tree2.Topic19 865 1.34 2 178 0 127
Tree2.Topic20 161 2.68 39 0 134
Tree2.Topic21 75 3.26 54 0 141
Tree2.Topic22 187 2.68 27 0 148
Tree2.Topic23 87 2.04 169 0 155
Tree2.Topic24 57 1.81 1 350 0 162
Tree2.Topic25 117 2.03 47 0 169
Tree2.Topic26 56 1.78 405 0 176
Tree2.Topic27 31 1.91 1 091 0 183
Tree2.Topic28 130 1.99 18 0 190
Tree2.Topic29 59 1.76 239 0 197
Tree2.Topic30 93 1.71 64 0 204
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