新媒体视域下个体投资用户的信息获取行为研究
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摘要
[目的 /意义]研究了大数据环境下个体投资者的信息获取行为偏好,探索新媒体环境对个体投资用户的决策影响。[方法/过程]基于开放式股票投资在线社交网络(OSN)的视角,分析、确定个体投资用户的主要信息获取行为,以及影响个体投资决策的两个重要因素;通过问卷调查收集相关数据,提出研究假设,进行数据分析,并运用回归分析方法进行假设检验,分析个体投资者决策的信息获取行为偏好。[结果/结论]研究发现:不同个体投资者对信息获取行为的选择存在明显差异;并且个人分析能力不同的投资者的行为偏好存在差异;个性化推荐是对个体投资者决策具有较大影响作用的信息获取行为。
[Purpose/Significance] The paper studied the preferences of individual investors for information acquisition behavior in the context of big data. And the paper explored the impact of the new media environment on individual investment users' decision-making. [Methods/Processes] Firstly,based on the perspective of the open stock investment online social network,the main information acquisition behavior of individual investors was analyzed,and two important factors that affect individual investment decisions were determined. Secondly,questionnaires were used to collect relevant data and research hypotheses were proposed. Finally,the paper used the regression analysis method to test the hypothesis,and analyzed the information acquisition behavior preference of individual investors' decision. [Results/Conclusion] The study found that there were significant differences in the choice of information acquisition behaviors among different individual investors. And there were differences in the behavioral preferences of investors with different personal analysis abilities. Moreover,personalized recommendation had a great influence on the individual investor decisions.
[Purpose/Significance] The paper studied the preferences of individual investors for information acquisition behavior in the context of big data. And the paper explored the impact of the new media environment on individual investment users' decision-making. [Methods/Processes] Firstly,based on the perspective of the open stock investment online social network,the main information acquisition behavior of individual investors was analyzed,and two important factors that affect individual investment decisions were determined. Secondly,questionnaires were used to collect relevant data and research hypotheses were proposed. Finally,the paper used the regression analysis method to test the hypothesis,and analyzed the information acquisition behavior preference of individual investors' decision. [Results/Conclusion] The study found that there were significant differences in the choice of information acquisition behaviors among different individual investors. And there were differences in the behavioral preferences of investors with different personal analysis abilities. Moreover,personalized recommendation had a great influence on the individual investor decisions.
引文
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[22]谭松涛,陈玉宇.投资经验能够改善股民的收益状况吗——基于股民交易记录数据的研究[J].金融研究,2012,(5):164-178.
[23]Xiao W.Does Practice Make Perfect?Evidence from Individual Investors'Experiences and Investment Returns[J].Journal of Interdisciplinary Mathematics,2015,18(6):811-825.
[24]卢佐冬.个体投资者心理与行为偏差研究[D].武汉:武汉大学,2012.
[25]张谊浩,李元,苏中锋,等.网络搜索能预测股票市场吗?[J].金融研究,2014,(2):193-206.
[26]Sabherwal S,Sarkar S K,Zhang Y.Do Internet Stock Message Boards Influence Trading?Evidence from Heavily Discussed Stocks with no Fundamental News[J].Journal of Business Finance&Accounting,2011,38(9-10):1209-1237.
[27]Guo Y,Yin C,Li M,et al.Mobile E-commerce Recommendation System Based on Multi-source Information Fusion for Sustainable E-business[J].Sustainability,2018,10(1):147.
[28]陈为东,王萍,王益成.学术新媒体环境下用户信息偶遇要素及内在机理研究[J].情报理论与实践,2017,(2):28-33.
[29]吴明隆.结构方程模型[M].重庆:重庆大学出版社,2013:467-475.
[2]刘虹,李煜,孙建军.基于微博微信的高校社交网络信息传播特征与效率对比分析[J].现代情报,2018,38(4):3-11.
[3]于灏,周玉成,井元伟,等.异质化带宽分配下的复杂网络数据流负载问题研究[J].物理学报,2013,62(8):12-18.
[4]于灏,马妍,王新华,等.带特定选择机制的供应系统网络模型构建及分析[J].系统工程学报,2017,32(5):686-698.
[5]Xia L L,Jiang G P,Song B,et al.Rumor Spreading Model Considering Hesitating Mechanism in Complex Social Networks[J].Physica A Statistical Mechanics&Its Applications,2015,437:295-303.
[6]阮逸润,老松杨,王竣德,等.一种改进的基于信息传播率的复杂网络影响力评估算法[J].物理学报,2017,20(66):285-294.
[7]杨善林,王佳佳,代宝,等.在线社交网络用户行为研究现状与展望[J].中国科学院院刊,2015,30(2):200-215.
[8]Cheung C M K,Liu I L B,Lee M K O.How Online Social Interactions Influence Customer Information Contribution Behavior in Online Social Shopping Communities:A Social Learning Theory Perspective[J].Journal of the Association for Information Science&Technology,2015,66(12):2511-2521.
[9]Lee C S,Ma L.News Sharing in Social Media:The Effect of Gratifications and Prior Experience[J].Computers in Human Behavior,2012,28(2):331-339.
[10]甘春梅,黄悦.社会化问答社区不同用户行为影响因素的实证研究[J].图书情报知识,2017,(6):114-124.
[11]付少雄,胡媛.大学生健康信息行为对实际健康水平的影响研究——基于健康素养与健康信息搜寻视角[J].现代情报,2018,(2):84-90.
[12]周朴雄,张兵荣,赵龙文.基于BP神经网络的情境化信息推荐服务研究[J].情报科学,2016,36(3):71-75.
[13]Wilson T D.Human Information Behavior[J].Informing Science the International Journal of An Emerging Transdiscipline,2000,3(2):49-56.
[14]Morris M R,Teevan J,Panovich K.A Comparison of Information Seeking Using Search Engines and Social Networks[C].International Conference on Weblogs and Social Media,2011,26(9):613-617.
[15]张迪,古俊生,邵若斯.健康信息获取渠道的聚类分析:主动获取与被动接触[J].国际新闻界,2015,(5):81-93.
[16]Kuhn H W,Morgenstern O,Rubinstein A.Theory of Games and Economic Behavior[M].Princeton University Press,2007,21(1):776.
[17]Liang H,Yang C,Zhang R,et al.Bounded Rationality,Anchoring-and-adjustment Sentiment,and Asset Pricing[J].North American Journal of Economics&Finance,2017,40:85-102.
[18]Tversky A,Tvsersky A.Prospect Theory:An Analysis of Decision-making Under Risk[J].Econometrica,1979,47(2):263-291.
[19]李月琳,刘济群.个体投资者投资决策中的信息利用行为研究[J].情报资料工作,2014,35(6):29-34.
[20]李月琳,胡玲玲.投资者信息行为分析:信息源的选择与利用研究[J].情报资料工作,2012,(4):90-97.
[21]West,Marie L.A mixed Methods Investigation Into Aspects of Medication Wastage in Malta[J].Journal of the Air&Waste Management Association,2015,65(10):1217-28.
[22]谭松涛,陈玉宇.投资经验能够改善股民的收益状况吗——基于股民交易记录数据的研究[J].金融研究,2012,(5):164-178.
[23]Xiao W.Does Practice Make Perfect?Evidence from Individual Investors'Experiences and Investment Returns[J].Journal of Interdisciplinary Mathematics,2015,18(6):811-825.
[24]卢佐冬.个体投资者心理与行为偏差研究[D].武汉:武汉大学,2012.
[25]张谊浩,李元,苏中锋,等.网络搜索能预测股票市场吗?[J].金融研究,2014,(2):193-206.
[26]Sabherwal S,Sarkar S K,Zhang Y.Do Internet Stock Message Boards Influence Trading?Evidence from Heavily Discussed Stocks with no Fundamental News[J].Journal of Business Finance&Accounting,2011,38(9-10):1209-1237.
[27]Guo Y,Yin C,Li M,et al.Mobile E-commerce Recommendation System Based on Multi-source Information Fusion for Sustainable E-business[J].Sustainability,2018,10(1):147.
[28]陈为东,王萍,王益成.学术新媒体环境下用户信息偶遇要素及内在机理研究[J].情报理论与实践,2017,(2):28-33.
[29]吴明隆.结构方程模型[M].重庆:重庆大学出版社,2013:467-475.