Decoding Twitter scraping for a merrier marketing
In the last couple of years, Twitter has been one of the most powerful platforms for an effective lead generation, viral advertising, and quality social network building. There are about 326 million active users on Twitter and it supports 40 languages. If you think about it, it is the best and the easiest way to reach the widest target groups. Given the user engagement and tweets from the pioneers of the industry, thought leaders, and monitoring your close competitors there are a ton of insights you can gather.
Social media scraping will help in tracking, analyzing, and putting this data into scrutiny. Twitter is the most happening platform and you can scrape twitter data to understand the user behavior, competitor strategy, make sentiment analysis, and stay updated with what’s happening on the globe’s most sought-after social channel from the tweets of people, peers, and companies that matter to you.
To get specific on this post, let’s all settle with the fact that while we agree and appreciate the importance of keeping a tab on this information, the most critical challenge in twitter scraping is the sheer volume of information and profiles.
Why Scrape data from Twitter?
Your data is not just a hand full of information that can be easily collected by reading and analyzing tweets, shares, likes, and interests of people and companies. The data is enormous and manually collecting them will not help you put your strategies to action within a reasonable time-frame.
Twitter holds data that is real-time and this information holds a lot of value to your business. If you are a digital marketer, think of how Twitter scraping will help you – all the influencers you can connect to, the competitors you can constantly monitor, the sentiment analysis you can perform, and the customer behavior study you can do.
5 Ways Twitter data helps your business.
Social media is where your customers rave about your brand when they love your product or service and tarnish it when they are dissatisfied. Twitter is powerful. Particularly, the millennials reach out to customer support for grievances and talk your brand up by tagging your handles. Twitter is where you can understand your customers, their needs, their honest opinions about you. Just think of all the insights you can gain by holding the customer views of your brand that will help you fine-tune your strategies.
The best way to get in touch with influencers would be through Twitter. There are higher chances of being successful in your efforts to reach out to them through Twitter DMs. This is because they’ve built a strong relationship with their followers and are always active posting content regularly. Scraping the influencers of your industry and their tweets will help you understand and analyze the content that goes viral, the ones that are shared the most. You can stay more aware of their tweet activities and reach out to them with more confidence knowing exactly about their interests and practices.
Your brand has a face and image in the social network. Particularly, on Twitter with the mentions that customers do to bring what they share about you to your notice, it is important that you track this data. Now, this mention goes as a notification to your profile, but when the number expands, there are automated replies to users. Scraping the mentions, be it good or bad, will help you understand the reputation, identify marketing opportunities, or even address dissatisfaction among your users and take steps towards it. This kind of scraping need not be done every day, but a weekly track of this information will help you constantly rework on your brand image and get better.
We design products for the customers and market it to ensure that it reaches the right audience and make sure that there are conversions. Twitter sentiment analysis will help you understand the overall experiences and opinions of your target section. Scraping their tweets, mentions, likes, shares, and other engagement will help you study the behavior and gauge on that opinion to understand trends. This data will help you make some big decisions like designing products, customizing it, cater to the real needs through effective marketing.
Instead of directly following your competitors to monitor their activities on Twitter, you can periodically scrape this data. This information will help you stay better informed of their strategies, the posts that attract engagement, their network and a lot of other insights. Analyzing this data will help you conclude the best practices and make the right decisions to stay ahead of your competition and keep a tab of their moves, which is necessary!
How does it work: Cracking the Twitter scraping code.
While Twitter is one of those places to help you gauge relevant information to get better with your strategies and decisions, it is not the only place. There are so many other platforms and mediums where the real-time exchange of news takes place. But. Twitter is one of the most influential platforms, given the number of users it has and the mounds of business opportunities it offers. So, you cannot afford to let go of the potential it holds for your business.
At Scrapeworks, we understand the significance of a platform like Twitter that holds value for your business.
We first understand the information or tweets you are looking to scrape and monitor. We research the relevant terms, hashtags, and keywords that are required to be scraped. This input is fed into our Scrapeworks platform and it will crawl tweets and other mentions or hashtags that is fed into it. This can be crawled daily, weekly, or monthly, at your convenience. We deliver this data in a structured format through APIs.
Let’s look at an example:
This use case is for a media service provider who is either starting out or is a competitor to a popular and successful media service provider, say Netflix. So, this sample python code here below is for scraping data from the Netflix twitter handle to scrape the latest ten posts. We can scrape any volume of data for deeper analysis.
The following sample code will extract the essential data points like hashtags – post – likes – retweets – photos of the Netflix handle on twitter up to ten posts. The data extracted would help in running an analysis to find out the type of content they share, what is the most engaging content, understanding the audience and a lot more.
The code for this use case would go like this:
sess = requests.Session() sess.headers['User-Agent'] = 'Mozilla/5.0 (Windows NT 6.3; WOW64; rv:38.0) Gecko/20100101 Firefox/38.0' url = "https://twitter.com/netflix" res = sess.get(url) data = res.content f=open("Cont.html","w") f.write("%s"%data) f.close() authorNameregex=re.compile(r'<span\s*class\=\"FullNameGroup\">\s*<strong[^>]*?>\s*([^>]*?)\s*<\/strong>',re.M|re.I|re.S) authorList=authorNameregex.findall(str(data)) for authors in authorList: print authors with open ("Twitter.txt", "a") as fh: fh.write ("%s"%authors+"\n")
The extracted output will be in a structured format thus enabling quick analysis:
Are you intimidated by the volumes of twitter profiles that you would require to scrape to make a solid working strategy for your study?
Scrapeworks is perfectly engineered to fulfill all your scraping needs. Everything from the volumes of data you need, to the well structured information you want; Scrapeworks can help you with the foundation of information that will help you elevate your analysis and marketing initiatives.You can set your parameters for the scraping requirements and we can deliver the data that you want. Go ahead and try Scrapeworks.
Crack the Twitter code with us and stay ahead of all the buzz by intelligently monitoring the most happening social channel of the planet.