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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mining-and-analyzing-linkedin-data/
课程评论：没有评论
课程名称：挖掘与分析LinkedIn数据 课程概述：LinkedIn是一种专注于职业经历的社交网络，旨在为来自不同领域的专业人士之间建立联系和关系。通过与全球的人们建立联系，专业人士可以提升自己的职业技能并寻找工作机会。另一方面，企业也可以根据用户提供的简历和技能搜索候选人。自2017年以来，LinkedIn已成为最大的商业平台，是专业人士和企业的重要战略工具。因此，专业人士必须懂得如何利用LinkedIn的数据为自己服务。LinkedIn提供了与用户个人资料相关的一些数据集，可以运用数据科学和分析技术提取关于人脉网络的重要见解。课程将解答诸如：“我们联系的人的主要职位是什么？”“哪些公司向我们的个人资料发送邀请？”“我们的联系人位于哪里？”以及“我想要工作的公司是否向我的个人资料发送邀请？”等问题，帮助学员分析个人网络与职业目标的一致性。 课程主要内容包括： - 使用LinkedIn API和.csv文件从个人资料中提取数据。如果没有LinkedIn账号，学员也可以使用课程提供的个人资料数据跟随学习。 - 提取和分析用户之间的连接、邀请和文本消息。 - 生成假数据以保护真实信息。 - 探索和可视化联系人所在公司的数据及职位信息。 - 使用Levenshtein距离、n-gram相似性和Jaccard距离来衡量字符串之间的相似性。 - 基于职位相似性对联系人进行聚类，并生成HTML视图以改善数据呈现。 - 使用位置API提取联系人的纬度和经度，以获取他们所居住的城市和国家。 - 动态查看联系人位置，使用Google Earth和Basemap库。 - 使用k均值算法对联系人进行聚类。 - 应用自然语言处理技术分析LinkedIn文本消息。 - 生成词云以查看最频繁的术语。 - 从文本消息中提取命名实体。 - 创建情感分类器，以提取LinkedIn消息的极性。 在课程中，我们将使用Python编程语言和Google Colab，因此学员无需在自己机器上安装任何软件，只需通过浏览器和互联网连接即可轻松跟随课程学习！这是第一次接触社交媒体数据分析的学员的最佳课程选择。
LinkedIn is a social network focused on professional experience in order to generate connections and relationships between professionals from different areas. Professionals can provide profissional skills and search for jobs by connecting with people around the world. For example, if you would like to work with Data Science you can connect with companies and people who work in this field, increasing your chances of getting a job. On the other hand, companies are able to search for candidates according to the curriculum and skills provided by users. In 2017, LinkedIn established itself as the largest business platform and an important strategic tool for both professionals and companies.It is important that professionals know how to use the data of this social network in their favor. LinkedIn provides some datasets related to your profile, in which it is possible to apply Data Science and Analysis techniques to extract important and interesting insights about our network of connections. We can answer questions like this: What are the main positions of the people who are connected to us? Which companies are sending invitations to our profile? What is the location of our contacts? Is our LinkedIn network made up of people and companies related to our job? Are the companies I want to work for sending invitations to my profile? These and other questions can be answered during this course, so you can analyze if your network is in line with what you want professionally. Below you can see the main topics that will be implemented step by step:Extract data from your LinkedIn profile using the LinkedIn API and.csv files. If you do not have LinkedIn, you will be able to follow the course using the data about my profileExtract and analyze connections between users, invitations and text messagesGenerate fake data to mask real informationExplore and visualize data related to your contacts' companies and job titlesUse Levenshtein distance, n-gram similarity and Jaccard distance to measure similarity between stringsCluster contacts based on similarity between positions, as well as generate HTML views to improve data presentationUse location APIs to extract latitude and longitude of contacts to capture the city and country they liveView the location of contacts dynamically with Google Earth and the Basemap libraryCluster contacts using k-means algorithmApply natural language processing techniques to analyze your LinkedIn text messagesGenerate word cloud to view the most frequent termsExtract named entities from your text messagesCreate a sentiment classifier to extract the polarity from LinkedIn messagesDuring the course, we will use the Python programming language and Google Colab, so you do not need to spend time installing the stuff on your own machine. You will be able to follow the course with a browser and an Internet connection! This is the best course if this is your first contact with social media data analysis!
