![]() Interested in learning about the LinkedIn API and would like to jump Startĭeveloping a LinkedIn professional network if you don’t already have oneĪs a worthwhile investment in your professional life.Īlthough most of the analysis in this chapter is performed against aĬomma-separated values (CSV) file of your LinkedIn connections that youĬan download, this section maintains continuity with other chapters in theīook by providing an overview of the LinkedIn API. The fundamental clustering techniques that you’ll learn about to otherĭomains, but this chapter won’t be quite as engaging since you can’tįollow along with the examples without your own LinkedIn data. If you don’t have a LinkedIn account, you can still apply Professional network to follow along with this chapter’s examples in a ![]() You’ll need a LinkedIn account and a handful of colleagues in your To a similarity measurement in order to answer the following kinds of LinkedIn API and introduces some fundamental data mining techniques that can The remainder of this chapter gets you set up to access data with the Requiring that you ask different types of questions about the data that’s To being modeled as a social graph like Facebook or Twitter, therefore The absence of such anĪPI method is intentional. Previous work positions, you cannot determine whether two arbitrary peopleĪre “mutually connected” as you could with Facebook. Your LinkedIn connections’ educational histories and While you can generally access all of the details about Opposed to arbitrary socializing and will necessarily be providing sensitiveĭetails about business relationships, job histories, and more. Principally interested in the business opportunities that it provides as Of the others we’ve looked at in this book. LinkedIn, its API has its own nuances that make it a bit different from many Given the somewhat sensitive nature of the data that’s tucked away at Might liken LinkedIn to a private event with a semiformal dress code whereĮveryone is on their best behavior and trying to convey the specific valueĪnd expertise that they could bring to the professional marketplace. If you liken Twitter to a busy public forum like a town squareĪnd Facebook to a very large room filled with friends and family chattingĪbout things that are (mostly) appropriate for dinner conversation, then you Other social network, the nature of its API data is inherently quiteĭifferent. Although LinkedIn may initially seem like any Tucked away at LinkedIn, a social networking site focused on professionalĪnd business relationships. This chapter introduces techniques and considerations for mining the troves of data ![]() URL of the LinkedIn Company Profile to target.Chapter 3. Mining LinkedIn: Faceting Job Titles, Clustering Colleagues, and true - Enable support for Company Profile URLs with numerical IDs.Ĭosts an extra 2 credit on top of the base cost of the endpoint. false (default value) - Will not resolve numerical IDs. This parameter accepts the following values: We achieve this by resolving numerical IDs into vanity IDs with cached company profiles from LinkDB.įor example, we will turn to - for which the API endpoint only supports the latter. * current (default) : lists current employeesĮnable support for Company Profile URLs with numerical IDs that you most frequently fetch from Sales Navigator. Parameter to tell the API to return past or current employees. When enrich_profiles=enrich, this parameter accepts value ranging from 1 to 100. The default value of this parameter is 200000.Īccepted values for this parameter is an integer ranging from 1 to 200000. Tune the maximum results returned per API call. (The base cost of calling this API endpoint with this parameter would be 10 credits.Įach employee matched and returned would cost 6 credits per employee returned.) The accepted value is a regular expression (regex). The default value of this parameter is null. * enrich: lists full profile of employeesĬalling this API endpoint with this parameter would add 1 credit per employee returned.įilter employees by their title by matching the employee's title against a regular expression. * skip (default): lists employee's profile url Get the full profile of employees instead of only their profile urls.Įach request respond with a streaming response of profiles. get ( api_endpoint, params = params, headers = header_dic ) URL Parameters Parameter Import requests api_endpoint = '' linkedin_profile_url = '' api_key = 'YOUR_API_KEY' header_dic = response = requests.
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