官方正版 新媒体数据分析与应用 微信数据分析微博数据分析抖音数据分析网络舆情数据分析 电子商务类专业新媒体营销课程教材
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书名:新媒体数据分析与应用
定价:49.8
ISBN:9787121425967
作者:无
版次:第1版
出版时间:2022-03
内容提要:
伴随着移动互联网、物联网技术的普及和成熟,依托数字技术的新媒体,如微信公众号、新浪微博、今日头条、抖音、喜马拉雅等,成为越来越多用户青睐的媒体形式。新媒体的发展,带来大量新媒体数据的积淀,有效分析新媒体数据能极大提高新媒体账户的业务效率和市场竞争力。本书系统性地给出新媒体数据如何准备、如何预处理、如何分析挖掘,新媒体数据的分析结果如何可视化,并以微信数据分析、微博数据分析、抖音数据分析、网络舆情数据分析和新媒体数据营销为案例,以常用的Excel为分析工具,详细地阐述新媒体数据分析的过程,旨在帮助读者提高新媒体数据分析的能力。本书适合作为普通高等本科院校及职业院校电子商务、市场营销、新闻与传播网络与新媒体专业的教材。
作者简介:
朱小栋,1981年生,安徽太湖人,上海理工大学副教授,管理科学与工程专业、国际贸易学专业、国际商务(专硕)专业研究生导师,中国计算机学会高级会员,2009年7月毕业于南京航空航天大学计算机应用技术专业,获工学博士学位。澳大利亚斯文本科技大学高级访问学者。公开发表论文60余篇,出版专著1篇,出版教材3篇。目前主持完成的主要纵向科研项目包括:***高等学校博士学科点专项科研基金项目1项,***人文社会科学青年基金项目1项,***重点实验室开放课题(安徽大学计算智能与信号处理重点实验室)1项,上海市市教委科研创新项目课题1项,主持完成上海高校外国留学生英语授课示范性课程1项。参与国家自然科学基金项目2项,参与国家社会科学基金项目1项。获上海市教学成果奖二等奖1次,中国机械工业科学技术奖二等奖一次。目前研究方向与研究兴趣: 大数据管理与数据挖掘;网络信息安全;国际电子商务。曾经参与主持过多个科研项目,其中有:1、201909,主持上海高校智库内涵建设项目:人工智能与大数据背景下上海布局的新思维与新举措。2、 201909,主持2019年上海高校大学计算机课程教学改革项目:"信息安全原理”进阶课程建设。3、201809-201902,主持上海市自贸区研究院(浦东智库研究院)智库研究项目:基于大数据与人工智能技术的上海市政府治理新思维与新举措。4、201809-201812, 主持360集团江苏复大科技有限公司委托科研课题:《信息安全原理与商务应用》编著建设研究。5、201807-201812, 主持上海高校智库内涵建设计划(战略研究)战略研究项目:基于云电子商务的上海市数字资源共享战略研究;6、201701-201712,主持2017年度上海理工大学"精品本科”系列教材建设项目:《UML与面向对象系统分析与设计》。7、2017.01-2017.12 主持上海理工大学教育发展2017年度教师教学发展研究项目,人文社科类本科生在全国挑战杯大挑竞赛中的竞争力研究。8、2015.12-2016.12 主持上海市教委出国访学资助计划,赴澳大利亚斯文本科技大学从事高级访问学者。
目录:
目 录
第 1 章 绪论 ····························································.1
1.1 数据分析的相关知识 ··································.2
1.2 新媒体与新媒体数据 ··································.5
1.3 新媒体数据分析的过程 ···························.10
本章知识小结 ·····················································.11
本章考核检测评价 ·············································.12
第 2 章 新媒体数据分析指标 ·························.13
2.1 新媒体数据分析指标体系 ·······················.14
2.2 数据运营维度 ············································.17
2.3 用户增长维度——以微信公众号
为例 ····························································.19
2.4 用户属性与互动维度——以微信
公众号为例 ················································.22
2.5 图文维度——以微信公众号为例 ···········.24
2.6 用户互动维度——以微信公众号
为例 ····························································.28
本章知识小结 ·····················································.29
本章考核检测评价 ·············································.29
第 3 章 新媒体数据的准备 ······························.31
3.1 新媒体数据来源 ········································.31
3.2 理解数据 ····················································.39
本章知识小结 ·····················································.42
本章考核检测评价 ·············································.42
第 4 章 新媒体数据的处理 ······························.44
4.1 数据清洗 ····················································.44
4.2 数据加工 ····················································.52
本章知识小结 ·····················································.59
本章考核检测评价 ·············································.59
第 5 章 新媒体数据的分析视角 ····················.61
5.1 现状分析 ····················································.61
5.2 原因分析 ····················································.65
5.3 预测分析 ····················································.71
本章知识小结 ·····················································.78
本章考核检测评价 ·············································.79
第 6 章 新媒体数据的可视化 ·························.80
6.1 可视化的意义 ············································.81
6.2 常用可视化图表 ········································.81
6.3 复杂图表 ····················································.97
6.4 利用编程语言绘图 ··································.122
本章知识小结 ···················································.124
本章考核检测评价 ···········································.124
第 7 章 微信数据分析 ·····································.125
7.1 微信数据分析概述 ··································.126
7.2 微信公众号数据分析 ······························.129
7.3 微信小程序数据分析 ······························.132
7.4 新榜数据分析平台 ··································.140
本章知识小结 ···················································.143
本章考核检测评价 ···········································.143
第 8 章 微博数据分析 ·····································.145
8.1 微博数据分析概述 ··································.145
8.2 微博基本数据分析 ··································.146
8.3 微博内容数据分析 ··································.151
8.4 微博粉丝数据分析 ··································.159
8.5 知微数据分析平台 ··································.164
本章知识小结 ···················································.170
本章考核检测评价 ···········································.170
第 9 章 抖音数据分析 ·····································.171
9.1 抖音数据分析概述 ··································.172
9.2 抖音基本数据分析 ··································.176
9.3 抖查查数据分析平台 ······························.180
9.4 飞瓜数据分析平台 ··································.183
本章知识小结 ···················································.189
本章考核检测评价 ···········································.189
第 10 章 网络舆情数据分析 ·························.190
10.1 网络舆情数据分析概述 ························.191
10.2 网络舆情基本数据分析 ························.193
10.3 新浪舆情通分析平台 ····························.205
本章知识小结 ···················································.208
本章考核检测评价 ···········································.209
参考文献 ··································································.210
定价:49.8
ISBN:9787121425967
作者:无
版次:第1版
出版时间:2022-03
内容提要:
伴随着移动互联网、物联网技术的普及和成熟,依托数字技术的新媒体,如微信公众号、新浪微博、今日头条、抖音、喜马拉雅等,成为越来越多用户青睐的媒体形式。新媒体的发展,带来大量新媒体数据的积淀,有效分析新媒体数据能极大提高新媒体账户的业务效率和市场竞争力。本书系统性地给出新媒体数据如何准备、如何预处理、如何分析挖掘,新媒体数据的分析结果如何可视化,并以微信数据分析、微博数据分析、抖音数据分析、网络舆情数据分析和新媒体数据营销为案例,以常用的Excel为分析工具,详细地阐述新媒体数据分析的过程,旨在帮助读者提高新媒体数据分析的能力。本书适合作为普通高等本科院校及职业院校电子商务、市场营销、新闻与传播网络与新媒体专业的教材。
作者简介:
朱小栋,1981年生,安徽太湖人,上海理工大学副教授,管理科学与工程专业、国际贸易学专业、国际商务(专硕)专业研究生导师,中国计算机学会高级会员,2009年7月毕业于南京航空航天大学计算机应用技术专业,获工学博士学位。澳大利亚斯文本科技大学高级访问学者。公开发表论文60余篇,出版专著1篇,出版教材3篇。目前主持完成的主要纵向科研项目包括:***高等学校博士学科点专项科研基金项目1项,***人文社会科学青年基金项目1项,***重点实验室开放课题(安徽大学计算智能与信号处理重点实验室)1项,上海市市教委科研创新项目课题1项,主持完成上海高校外国留学生英语授课示范性课程1项。参与国家自然科学基金项目2项,参与国家社会科学基金项目1项。获上海市教学成果奖二等奖1次,中国机械工业科学技术奖二等奖一次。目前研究方向与研究兴趣: 大数据管理与数据挖掘;网络信息安全;国际电子商务。曾经参与主持过多个科研项目,其中有:1、201909,主持上海高校智库内涵建设项目:人工智能与大数据背景下上海布局的新思维与新举措。2、 201909,主持2019年上海高校大学计算机课程教学改革项目:"信息安全原理”进阶课程建设。3、201809-201902,主持上海市自贸区研究院(浦东智库研究院)智库研究项目:基于大数据与人工智能技术的上海市政府治理新思维与新举措。4、201809-201812, 主持360集团江苏复大科技有限公司委托科研课题:《信息安全原理与商务应用》编著建设研究。5、201807-201812, 主持上海高校智库内涵建设计划(战略研究)战略研究项目:基于云电子商务的上海市数字资源共享战略研究;6、201701-201712,主持2017年度上海理工大学"精品本科”系列教材建设项目:《UML与面向对象系统分析与设计》。7、2017.01-2017.12 主持上海理工大学教育发展2017年度教师教学发展研究项目,人文社科类本科生在全国挑战杯大挑竞赛中的竞争力研究。8、2015.12-2016.12 主持上海市教委出国访学资助计划,赴澳大利亚斯文本科技大学从事高级访问学者。
目录:
目 录
第 1 章 绪论 ····························································.1
1.1 数据分析的相关知识 ··································.2
1.2 新媒体与新媒体数据 ··································.5
1.3 新媒体数据分析的过程 ···························.10
本章知识小结 ·····················································.11
本章考核检测评价 ·············································.12
第 2 章 新媒体数据分析指标 ·························.13
2.1 新媒体数据分析指标体系 ·······················.14
2.2 数据运营维度 ············································.17
2.3 用户增长维度——以微信公众号
为例 ····························································.19
2.4 用户属性与互动维度——以微信
公众号为例 ················································.22
2.5 图文维度——以微信公众号为例 ···········.24
2.6 用户互动维度——以微信公众号
为例 ····························································.28
本章知识小结 ·····················································.29
本章考核检测评价 ·············································.29
第 3 章 新媒体数据的准备 ······························.31
3.1 新媒体数据来源 ········································.31
3.2 理解数据 ····················································.39
本章知识小结 ·····················································.42
本章考核检测评价 ·············································.42
第 4 章 新媒体数据的处理 ······························.44
4.1 数据清洗 ····················································.44
4.2 数据加工 ····················································.52
本章知识小结 ·····················································.59
本章考核检测评价 ·············································.59
第 5 章 新媒体数据的分析视角 ····················.61
5.1 现状分析 ····················································.61
5.2 原因分析 ····················································.65
5.3 预测分析 ····················································.71
本章知识小结 ·····················································.78
本章考核检测评价 ·············································.79
第 6 章 新媒体数据的可视化 ·························.80
6.1 可视化的意义 ············································.81
6.2 常用可视化图表 ········································.81
6.3 复杂图表 ····················································.97
6.4 利用编程语言绘图 ··································.122
本章知识小结 ···················································.124
本章考核检测评价 ···········································.124
第 7 章 微信数据分析 ·····································.125
7.1 微信数据分析概述 ··································.126
7.2 微信公众号数据分析 ······························.129
7.3 微信小程序数据分析 ······························.132
7.4 新榜数据分析平台 ··································.140
本章知识小结 ···················································.143
本章考核检测评价 ···········································.143
第 8 章 微博数据分析 ·····································.145
8.1 微博数据分析概述 ··································.145
8.2 微博基本数据分析 ··································.146
8.3 微博内容数据分析 ··································.151
8.4 微博粉丝数据分析 ··································.159
8.5 知微数据分析平台 ··································.164
本章知识小结 ···················································.170
本章考核检测评价 ···········································.170
第 9 章 抖音数据分析 ·····································.171
9.1 抖音数据分析概述 ··································.172
9.2 抖音基本数据分析 ··································.176
9.3 抖查查数据分析平台 ······························.180
9.4 飞瓜数据分析平台 ··································.183
本章知识小结 ···················································.189
本章考核检测评价 ···········································.189
第 10 章 网络舆情数据分析 ·························.190
10.1 网络舆情数据分析概述 ························.191
10.2 网络舆情基本数据分析 ························.193
10.3 新浪舆情通分析平台 ····························.205
本章知识小结 ···················································.208
本章考核检测评价 ···········································.209
参考文献 ··································································.210
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