Bursty topic detection method for microblog based on influence from user behaviors

doi:10.3969/j.issn.0253-2778.2017.04.007

Abstract

Abstract: Social networks are becoming more and more popular where people can post anything anytime. Due to the huge user community, social network data is increasing with each passing day. Therefore how to explore the knowledge in huge data seems to be hard work. As microblog has time-related characteristics and social network behavior attributes, momentum signal enhancement model is put forward to detect bursty microblog topics effectively. Influence factor and hot energy factor are put forward to improve the momentum model. The influence factor uses the data before the current point but within a given period to calculate the

Key words: bursty topic, momentum, signal enhancement, hot energy； influence

CLC Number:

TP391

WAN Yue, SUI Jie. Bursty topic detection method for microblog based on influence from user behaviors[J]. Journal of University of Science and Technology of China, 2017, 47(4): 328-335.

References

［1］
GAGLIO S, RE G L, MORANA M. A framework for real-time Twitter data analysis[J]. Computer Communications, 2016, 73: 236-242.
[2] FUNG G P C, YU J X, YU P S, et al. Parameter free bursty events detection in text streams[C]// Proceedings of the 31st International Conference on Very large Data Bases. Trondheim, Norway: VLDB Endowment, 2005: 181-192.
[3] DIAO Q M, JIANG J, ZHU F D, et al. Finding bursty topics from microblogs[C]// Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics. Jeju Island, Korea: Association for Computational Linguistics, 2012: 536-544.
[4] 于海峰, 王延章, 卢小丽, 等. 基于知识元的突发事件风险熵预测模型研究[J]. 系统工程学报, 2016, 31(1): 117-126.
YU Haifeng, WANG Yanzhang, LU Xiaoli, et al. Emergency risk entropy forecasting model based on knowledge element[J]. Journal of Systems Engineering, 2016, 31(1): 117-126.
[5] KLEINBERG J. Bursty and hierarchical structure in streams[J]. Data Mining and Knowledge Discovery, 2003, 7(4): 373-397.
[6] CHEN Y, YANG S, CHENG X Q. Bursty topics extraction for web forums[C]// Proceedings of the 11th International Workshop on Web Information and Data Management. Hong Kong, China: ACM Press, 2009: 55-58.
[7] HE D, PARKER D S. Topic momentums: An alternative model of bursts in streams of topics[C]// Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Washington D C, USA: ACM Press, 2010: 443-452.
[8] 贺敏, 杜攀, 张瑾,等. 基于动量模型的微博突发话题检测方法[J]. 计算机研究与发展, 2015, 52(5): 1022-1028.
HE Min, DU Pan, ZHANG Jin, et al. Microblog bursty topic detection method based on momentum model[J]. Journal of Computer Research and Development, 2015, 52(5): 1022-1028.
[9] HE D, PARKER D S. Learning the funding momentum of research projects[J]. Knowledge Discovery and Data Mining, 2011, 6635(2):532-543.
[10] DU Y, HE Y, TIAN Y, et al. Microblog bursty topic detection based on user relationship[C]// Proceedings of the 6th IEEE Joint International Information Technology and Artificial Intelligence Conference. Chongqing, China: IEEE Press, 2011, 1: 260-263.
[11] 王征, 王林森, 赵磊. 基于信息密度的微博突发话题检测模型研究[J]. 情报理论与实践, 2016, 39(3): 125-129.
[12] 申国伟, 杨武, 王巍,等. 面向大规模微博消息流的突发话题检测[J]. 计算机研究与发展, 2015, 52(2): 512-521.
SHEN Guowei, YANG Wu, WANG Wei, et al. Burst topic detection oriented large-scale microblogs streams[J]. Journal of Computer Research and Development, 2015, 52(2): 512-521.
[13] 贺敏, 徐杰, 杜攀, 等. 基于时间序列分析的微博突发话题检测方法[J]. 通信学报, 2016, 37(3): 48-54.
HE Min, XU Jie, DU Pan, et al. Bursty topic detection method for microblog based on time series analysis[J]. Journal on Communications, 2016, 37(3): 48-54.
[14] 郭跇秀, 吕学强, 李卓. 基于突发词聚类的微博突发事件检测方法[J]. 计算机应用, 2014, 34(2): 486-490, 505.
GUO Yixiu, LYN Xueqiang, LI Zhuo. Bursty topics detection approach on Chinese microblog based on burst words clustering[J]. Journal of Computer Applications, 2014, 34(2): 486-490, 505.
[15] 徐志明, 李栋, 刘挺, 等. 微博用户的相似性度量及其应用[J]. 计算机学报, 2014, 37(1): 207-218.
XU Zhiming, LI Dong, LIU Ting, et al. Measuring similarity between microblog users and its application[J]. Chinese Journal of Computers, 2014, 37(1): 207-218.
[16] 毛佳昕, 刘奕群, 张敏, 等. 基于用户行为的微博用户社会影响力分析[J]. 计算机学报, 2014, 37(4): 791-800.
MAO Jiaxin, LIU Yiqun ZHANG Min, et al. Social influence analysis for micro-blog user based on user behavior[J]. Chinese Journal of Computers, 2014, 37(4): 791-800.
[17] 陈克寒, 韩盼盼, 吴健. 基于用户聚类的异构社交网络推荐算法[J]. 计算机学报, 2013, 36(2): 349-359.
CHEN Kehan, HAN Panpan, WU Jian. User clustering based social network recommendation[J]. Chinese Journal of Computers, 2013, 36(2): 349-359.

（上接第303页）

[8] 余伟, 李石君, 杨莎, 等. Web大数据环境下的不一致跨源数据发现[J]. 计算机研究与发展, 2015, 52(2): 295-308.
YU Wei, LI Shijun, YANG Sha, et al. Automatically discovering of inconsistency among cross-source Data based on Web big Data[J]. Journal of Computer Research and Development, 2015, 52(2): 295-308.
[9] 张安珍,门雪莹,王宏志,等.大数据上基于Hadoop的不一致数据检测与修复算法[J]. 计算机科学与探索, 2015, 9(9): 1044-1055.
[10] 金连,王宏志,黄沈滨,等.基于Map-Reduce的大数据缺失值填充算法[J]. 计算机研究与发展, 2013, 50: 312-321.
[11] 罗元剑,姜建国,王思叶,等.基于有限状态机的RFID流数据过滤与清理技术[J].软件学报, 2014, 25(8): 1713-1728.
LUO Yuanjian, JIANG Jianguo, WANG Siye, et al. Filtering and cleaning for RFID streaming Data technology based on finite state machine[J]. Journal of Software, 2014, 25(8): 1713-1728.
[12] 陈振国，田立勤. 信任模型在雾霾感知源评价中的应用[J].计算机应用, 2016, 36(2): 472-477.
CHEN Zhenguo, TIAN Liqin. Application of trust model in evaluation of haze perception source[J]. Journal of Computer Applications, 2016, 36(2): 472-477.
[13] 罗涛,李俊涛,刘瑞娜,等.VANET中安全信息的快速可靠广播路由算法[J].计算机学报, 2015, 38(3): 663-672.
LUO Tao, LI Juntao, LIU Ruina, et al. A fast and reliable broadcast routing algorithm for safety related information in VANET[J]. Chinese Journal of Computers, 2015, 38(3): 663-672.
[14] 田立勤,林闯, 张琪,等.物联网监测拓扑可靠性设计与优化分析[J].软件学报, 2014, 25(8): 1625-1639.
TIAN Liqin, LIN Chuang, ZHANG Qi, et al. Topology reliability design and optimization analysis of IoT-based monitoring[J]. Journal of Software, 2014, 25(8): 1625-1639.
[15] 钟晓睿,马春光.基于动态累加器的异构传感网认证组密钥管理方案[J]. 通信学报, 2014, 35(3): 124-134.
ZHONG Xiaorui, MA Chunguang. Dynamic accumulators-based authenticated group key management scheme for heterogeneous wireless sensor network[J]. Journal on Communications, 2014, 35(3): 124-134.

[1]	ZHAN Yongkun, YANG Wenfei, ZHANG Tianzhu. Relation aware network for weakly-supervised temporal action localization [J]. Journal of University of Science and Technology of China, 2021, 51(10): 753-765.
[2]	Liang Qipeng, Zhu Qiaohui, Kang Yu, Zhao YunBo. Estimation based approximating control for wireless networked control systems [J]. Journal of University of Science and Technology of China, 2021, 51(4): 327-334.
[3]	Li Huicong, Fu Xiaoming∗ . Anisotropic surface meshing using locally isometric embedding [J]. Journal of University of Science and Technology of China, 2020, 50(12): 1460-1471.
[4]	YU Jun, LI Yajie, CHENG Lilei, LIAN Shun, TAN Chang, DING Decheng, Liu Qi. Research and practice of plagiarism detection in program code assignments by college students [J]. Journal of University of Science and Technology of China, 2020, 50(8): 1048-1057.
[5]	ZHANG Wenjing, BAN Zhijie. Citation network’s influence maximization algorithm based on global influence [J]. Journal of University of Science and Technology of China, 2020, 50(8): 1058-1063.
[6]	REN Min, XU Ling, WANG Feng, WU Chao. Campus encyclopedia platform based on knowledge recommendation [J]. Journal of University of Science and Technology of China, 2020, 50(8): 1072-1076.
[7]	SUN Lei, ZHANG Yining, XUE Yanfang, QIAO Lishan, ZHANG Limei. Adaptive functional connectivity network learning and application in brain disorders identification [J]. Journal of University of Science and Technology of China, 2020, 50(8): 1102-1109.
[8]	BAI Jiangbo, YANG Yang, ZHANG Wensheng. A simulation of the synthetic aperture radar image based on improved CycleGAN [J]. Journal of University of Science and Technology of China, 2020, 50(8): 1181-1186.
[9]	XIN Shouyu, ZHENG Ruirui, ZHOU Yu, LIU Wenpeng, HE Jianjun. A one-shot learning algorithm using support set information during training [J]. Journal of University of Science and Technology of China, 2020, 50(8): 1187-1192.
[10]	WANG Zhihua, KANG Hongmei. Using splines on triangular mesh to solve PDE with nonhomogeneous boundary [J]. Journal of University of Science and Technology of China, 2020, 50(7): 901-905.
[11]	GONG Lejun , ZHOU Shehai, CHENG Yifei, GAO Zhihong, LI Huakang. Identification of PBMC-related cells of single cell RNA sequence data [J]. Journal of University of Science and Technology of China, 2020, 50(7): 1013-1018.
[12]	DU Shuying, DU Peng, DING Shifei. A malicious domain name detection method based on CNN [J]. Journal of University of Science and Technology of China, 2020, 50(7): 1019-1025.
[13]	LI Yongjun, CAO Weihua, LING Qiang. A multi-target tracking algorithm based on feature point trajectories [J]. Journal of University of Science and Technology of China, 2020, 50(6): 726-732.
[14]	. A modified coherent diffraction algorithm based on the total variation algorithm for insufficient data [J]. Journal of University of Science and Technology of China, 2020, 50(4): 418-427.
[15]	WANG Xuhui, YAN Mingye, WU Meng. Suitable for the construction of degenerate smooth interpolated surfaces patches in isogeometric analysis [J]. Journal of University of Science and Technology of China, 2020, 50(3): 335-342.