JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2024, Vol. 59 ›› Issue (9): 108-118.doi: 10.6040/j.issn.1671-9352.0.2023.334

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A method of online teaching platform selection based on online reviews

Xia LIANG(),Jie GUO*()   

  1. School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, Shandong, China
  • Received:2023-07-28 Online:2024-09-20 Published:2024-10-10
  • Contact: Jie GUO E-mail:susanliangxia@163.com;guojie@mail.sdufe.edu.cn

Abstract:

To better select online teaching platforms, give college students a better online course learning experience, and provide a reference for future online education and teaching, a method for selecting online teaching platforms based on online reviews is proposed. Firstly, user reviews from alternative online teaching platforms are collected by the crawler technology, and NLPIR-ICTCLAS Chinese word separation system is used to separate online words. Next, attribute word extraction is conducted using TF-IDF algorithm, along with a method that was manually selected to obtain the attribute set. The weights of attributes are determined using the mean square deviation method. Subsequently, sentiment analysis is carried out on the online reviews, with user emotional orientations represented as probability distributions regarding the evaluation scale. On this basis, the extended VIKOR method is used to select the optimal online teaching platform. Finally, the feasibility of the method proposed in this paper is demonstrated through an example and comparative analysis.

Key words: online teaching platform, online review, sentiment analysis, TF-IDF algorithm

CLC Number: 

  • C934

Table 1

Some emotional words and emotional attitudes"

情感态度 情感词
E+   完美、全、丰富、划算、值得、好、满意、可信赖、赞、合理、称心如意、多、名不虚传、丰厚、显著、负责、上头、便宜、周到、负责, 专业、方便、灵活、容易、纯正、耐心、nice等
E 一般、还行、凑合、很正常、差不多、普通、还可以等
E- 贵、垃圾、鸡肋、少、差、差评、破、欺骗、太难了、糊弄、烦、反感、过分、恶劣、头疼、five等

Table 2

Degree words and their corresponding weights"

分值 程度词
1 有点、颇为、稍微、挺、些微、多少、有些、略、略微、比较、较为、颇、蛮、过于、较、巨
2   很、最、非常、尤为、绝对、过于、很、相当、超、特别、分外、十分、甚、尤其、无比、更、越、更加、老、格外、惊人地、灰常、极、太、至、超级、very

Table 3

Evaluation of m alternative options regarding attribute Bj"

H A1 A2 Am
H1 p1j1 p2j1 pmj1
H2 p1j2 p2j2 pmj2
H3 p1j3 p2j3 pmj3
H4 p1j4 p2j4 pmj4
H5 p1j5 p2j5 pmj5

Table 4

Attribute terms and their TF-IDF values"

属性词 TF-IDF值 属性词 TF-IDF值
广告 0.570 643 942 287 151 80 功能 0.073 945 348 040 433 440
软件 0.424 827 148 550 505 70 电脑 0.068 936 544 982 383 900
视频 0.241 131 954 399 649 16 学校 0.064 617 177 402 105 260
课程 0.233 154 040 135 521 16 客服 0.062 628 465 681 981 420
手机 0.165 600 998 484 127 96 摄像头 0.062 365 549 569 659 444
后台 0.105 635 165 620 433 43 太卡 0.061 686 106 826 109 390
分屏 0.098 697 770 921 775 02 版本 0.054 769 831 545 521 160
课堂 0.092 985 846 478 328 17 界面 0.054 127 692 586 749 224

Table 5

Set of attributes"

属性 平台广告量 平台服务 平台资源 平台稳定性 平台适应性
符号 B1 B2 B3 B4 B5

Table 6

Distribution of the 4 alternative options concerning attribute B1"

H A1 A2 A3 A4
-2 5/13 0 78/125 0
-1 8/13 0 8/25 0
0 0 1 6/125 1
1 0 0 1/125 0
2 0 0 0 0

Table 7

Distribution of the 4 alternative options concerning attribute B2"

H A1 A2 A3 A4
-2 0 3/7 0 1/9
-1 7/8 3/7 0 7/9
0 1/8 1/7 1 1/9
1 0 0 0 0
2 0 0 0 0

Table 8

Distribution of the 4 alternative options concerning attribute B3"

H A1 A2 A3 A4
-2 2/47 0 0 0
-1 13/47 1/8 1/3 2/7
0 13/47 1/2 1/2 11/35
1 7/47 3/8 1/6 9/35
2 12/47 0 0 1/7

Table 9

Distribution of the 4 alternative options concerning attribute B4"

H A1 A2 A3 A4
-2 2/39 3/13 1/5 7/27
-1 7/13 5/13 3/10 8/27
0 11/39 4/13 2/5 8/27
1 4/39 1/13 1/10 1/9
2 1/39 0 0 1/27

Table 10

Distribution of the 4 alternative options concerning attribute B5"

H A1 A2 A3 A4
-2 5/34 2/21 5/21 3/28
-1 7/34 3/7 8/21 13/28
0 9/34 4/21 4/21 1/7
1 9/34 2/7 1/7 2/7
2 2/17 0 1/21 0

Table 11

Expected evaluation values for each alternative under different attributes"

H A1 A2 A3 A4
B1 -1.38 0 -1.56 0
B2 -0.88 -1.29 0 -1.00
B3 0.30 0.25 -0.17 0.26
B4 -0.49 -0.77 -0.60 -0.63
B5 0.00 -0.33 -0.62 -0.39

Table 12

Probability distributions of individual components in the positive ideal solutionZ+"

正理想解 H
-2 -1 0 1 2
z1+ 0 0 124/125 1/125 0
z2+ 0 6/7 1/7 0 0
z3+ 0 0 139/376 3/8 12/47
z4+ 0 61/135 2/5 1/9 1/27
z5+ 0 41/102 9/34 2/7 1/21

Table 13

Probability distributions of individual components in the positive ideal solution Z -"

负理想解 H
-2 -1 0 1 2
z1- 78/125 47/125 0 0 0
z2- 3/7 4/7 0 0 0
z3- 2/47 1/3 1/2 35/282 0
z4- 7/27 7/13 71/351 0 0
z5- 5/21 1/2 11/42 0 0

Table 14

Group utility values and individual regret values for the distances between the four alternatives"

备选方案 A1 A2 A3 A4
Ui 0.351 3 0.416 4 0.976 4 0.275 5
Ri 0.233 6 0.203 3 0.406 5 0.083 3

Table 15

Compromise assessment values based on the distances from the four alternative options"

备选方案 A1 A2 A3 A4
Ti 0.286 5 0.286 0 1 0

Fig.1

Ranking results of alternative options under different parameter settings"

1 毕建武, 刘洋, 樊治平. 依据在线评论的商品排序方法[J]. 系统工程学报, 2018, 33 (3): 422- 432.
BI Jianwu , LIU Yang , FAN Zhiping . Method for ranking products through online reviews[J]. Journal of Systems Engineering, 2018, 33 (3): 422- 432.
2 由丽萍, 何玲玲. 基于框架语义的在线医疗评论情感分析[J]. 现代情报, 2020, 40 (3): 111-116, 125.
YOU Liping , HE Lingling . Sentiment analysis of medical online comments based on frame semantics[J]. Journal of Modern Information, 2020, 40 (3): 111-116, 125.
3 常青, 杨武健. 在线教育产品评论与用户使用意愿的关系[J]. 图书情报工作, 2020, 64 (17): 1- 10.
CHANG Qing , YANG Wujian . The relationship between online education product reviews and users' willingness to use[J]. Library and Information Service, 2020, 64 (17): 1- 10.
4 王安宁, 张强, 彭张林, 等. 在线评论的行为影响与价值应用研究综述[J]. 中国管理科学, 2021, 29 (12): 191- 202.
WANG Anning , ZHANG Qiang , PENG Zhanglin , et al. A review of behavioral influence and value application for online reviews[J]. Chinese Journal of Management Science, 2021, 29 (12): 191- 202.
5 李杨, 徐泽水, 王新鑫. 基于在线评论的情感分析方法及应用[J]. 控制与决策, 2023, 38 (2): 304- 317.
LI Yang , XU Zeshui , WANG Xinxin . Methods and applications of sentiment analysis with online reviews[J]. Control and Decision, 2023, 38 (2): 304- 317.
6 YANG Xian , YANG Guangfei , WU Jiangning . Integrating rich and heterogeneous information to design a ranking system for multiple products[J]. Decision Support Systems, 2016, 84, 117- 133.
doi: 10.1016/j.dss.2016.02.009
7 梁霞, 姜艳萍, 高梦. 基于在线评论的产品选择方法[J]. 东北大学学报(自然科学版), 2017, 38 (1): 143- 147.
LIANG Xia , JIANG Yanping , GAO Meng . Product selection methods based on online reviews[J]. Journal of Northeastern University (Natural Science), 2017, 38 (1): 143- 147.
8 DARKO A P , LIANG D C . A heterogeneous opinion-driven decision-support model for tourists' selection with different travel needs in online reviews[J]. Journal of the Operational Research Society, 2023, 74 (1): 272- 289.
doi: 10.1080/01605682.2022.2035274
9 尤天慧, 张瑾, 樊治平. 基于在线评价信息和消费者期望的商品选择方法[J]. 中国管理科学, 2017, 25 (11): 94- 102.
YOU Tianhui , ZHANG Jin , FAN Zhiping . Method for selecting desirable product(s) based on online rating information and customer's aspirations[J]. Chinese Journal of Management Science, 2017, 25 (11): 94- 102.
10 TIAN Zhangpeng , LIANG Heming , NIE Ruxin , et al. Data-driven multi-criteria decision support method for electric vehicle selection[J]. Computers & Industrial Engineering, 2023, 177, 109061.
11 LIANG Xia , GUO Jie , SUN Yan , et al. A method of product selection based on online reviews[J]. Mobile Information Systems, 2021, 9656315, 1- 16.
12 刘旭旺, 王骏嘉, 齐微, 等. 基于在线评论的产品上市模式选择策略研究[J]. 系统工程, 2023,
LIU Xuwang , WANG Junjia , QI Wei , et al. Product launch mode selection strategy based on online reviews[J]. Systems Engineering, 2023,
13 张培行. 基于在线评论文本分析的汽车产品选择方法研究[D]. 合肥: 合肥工业大学, 2019.
ZHANG Peihang. Research on automobile product selection method based on online comment text analysis[D]. Hefei: Hefei University of Technology, 2019.
14 BI Jianwu , LIU Yang , FAN Zhiping . Representing sentiment analysis results of online reviews using interval type-2 fuzzy numbers and its application to product ranking[J]. Information Sciences, 2019, 504, 293- 307.
doi: 10.1016/j.ins.2019.07.025
15 NIE Ruxin , TIAN Zhangpeng , WANG Jianqiang , et al. Hotel selection driven by online textual reviews: applying a semantic partitioned sentiment dictionary and evidence theory[J]. International Journal of Hospitality Management, 2020, 88, 1- 16.
16 ZHANG Dong , WU Chong , LIU Jiaming . Ranking products with online reviews: a novel method based on hesitant fuzzy set and sentiment word framework[J]. Journal of the Operational Research Society, 2020, 71 (3): 528- 542.
doi: 10.1080/01605682.2018.1557021
17 赵宇晴, 阮平南, 刘晓燕, 等. 基于在线评论的用户满意度评价研究[J]. 管理评论, 2020, 32 (3): 179- 189.
ZHAO Yuging , RUAN Pingnan , LIU Xiaoyan , et al. Study on user satisfaction evaluation based on online comment[J]. Management Review, 2020, 32 (3): 179- 189.
18 史达, 王乐乐, 衣博文. 在线评论有用性的深度数据挖掘: 基于TripAdvisor的酒店评论数据[J]. 南开管理评论, 2020, 23 (5): 64- 75.
SHI Da , WANG Lele , YI Bowen . Deep data mining for online reviews usefulness: hotel reviews data on TripAdvisor[J]. Nankai Business Review, 2020, 23 (5): 64- 75.
19 贾文军, 郭玉婷, 赵泽宁. 大学生在线学习体验的聚类分析研究[J]. 中国高教研究, 2020, (4): 23- 27.
JIA Wenjun , GUO Yuting , ZHAO Zening . Clustering analysis of college students' online learning experience[J]. China Higher Education Research, 2020, (4): 23- 27.
20 程龙. 基于改进TF-IDF算法的信息抽取系统设计与实现[D]. 北京邮电大学, 2019.
CHENG Long. Design and implementation of information extraction system based on improved TF-IDF algorithm[D]. Beijing University of Posts and Telecommunications, 2019.
21 王根生, 黄学坚. 基于Word2vec和改进型TF-IDF的卷积神经网络文本分类模型[J]. 小型微型计算机系统, 2019, 40 (5): 1120- 1126.
WANG Gensheng , HUANG Xuejian . Convolution neural network text classification model based on Word2Vec and improved TF-IDF[J]. Journal of Chinese Computer Systems, 2019, 40 (5): 1120- 1126.
22 ZHUO Zhou , QIN Jiaohua , XIANG Xuyu , et al. News text topic clustering optimized method based on TF-IDF algorithm on spark[J]. CMC: Computers, Materials & Continua, 2020, 62 (1): 217- 231.
23 LIU Yang , BI Jianwu , FAN Zhiping . Ranking products through online reviews: a method based on sentiment analysis technique and intuitionistic fuzzy set theory[J]. Information Fusion, 2016, 36, 149- 161.
24 JIANG Yanping , LIANG Haiming , SUN Minghe . A method for discrete stochastic MADM problems based on the ideal and nadir solutions[J]. Computers & Industrial Engineering, 2015, 87, 114- 125.
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