Data Mining: Social Media vs. Online Communities

Businesses trying to better align themselves with customer requirements should take advantage of social media, which is clearly a rich source of raw, unfiltered consumer data. Online communities, on the other hand, can work in a similar way and are specifically designed to collect data for research. So, which platform is superior for data mining? What do you prefer: social media or online communities?

Mining Social Media

Data mining is an amazing option for extracting predictive knowledge from this easily available supply of consumer information. According to one study on social media data mining, researchers were able to "predict the impact of an individual published post" and allow businesses to "[tailor] the advertising of products and services better." According to this study, making the most of every post enhances earnings since the forecasts allow marketers adjust each post to be more influential on the intended audience. Because these posts are many potential customers' first point of contact, increasing public awareness through promotions and reviews on social media channels will pique their interest and attract them to learn more about the firm and its other items. While this strategy is simple, it can have a significant influence on the bottom line.

There have been a few prominent resources on how to mine social media information for the purpose of social intelligence within a corporation. Sandra Gittlen's post on CIO goes into great detail about how social media may be utilised to inform marketing decisions and increase sales or brand awareness for a business. This is a really helpful byproduct of social media data mining, and Gittlen believes that many brands aren't taking advantage of it as much as they could be. Data mining identifies profitable prospects that aren't immediately apparent, as well as findings that reduce the risk factor in specific campaigns or promotions.

Data mining allows the researcher to find meaningful patterns of information from social media activity through forums, review pages, and general posts regarding the company in question. Companies can be more rely on the information acquired and results supplied by this single method of information analysis because the data collected comes from a source that gives direct contact with customer opinions.

Scraping is the most common method of gathering this information for data mining purposes. Web scraping simulates how a human might explore the internet for information, which may subsequently be analysed for market research purposes. When and what can be scraped on social media and other websites are governed by rules. These rules can be accessed by putting in the website address, such as ‘facebook.com,' and then adding ‘/robot.txt' to the end. The rules and regulations for scraping that specific website will be displayed. However, following the Cambridge Analytics scandal in March, general data privacy standards have been dramatically strengthened, making it more difficult for businesses to collect the massive amounts of data required from social media.

Mining Online Communities

Consent is a significant distinction when scraping data from social media and online forums. Since the Cambridge Analytica scandal, Facebook has enacted rules that allow you to only scrape public (and private by individual consent) data at certain times of the day when traffic is lower; this ensures that the data collected is voluntary and won't negatively impact the social media channel's performance. Because of the numerous complications surrounding consent, this is where online communities shine.

Data mining allows researchers to analyse a significant amount of data acquired from a customised online community when it comes to online conversations, insight communities, and other collaborative conversation tools. Researchers can then select their target audience and invite those who meet the requirements to participate in the study.

Instead of digging through the data, researchers will be able to ask the invited audience members questions about their opinions and desires, and the data mining tool would pick up on the key terms and trends in all of their responses. Participants have more freedom in forums and blogs, but because this is a dedicated research platform, it's likely that these debates will still be on relevant issues. Participants may even ask questions that were not included in the original scope, which is ideal for passive data collection.

Which platform is best for data mining?

Social media reduces participant involvement, which can be both beneficial and detrimental. With this in mind, it is feasible to reach customers who would otherwise not join in online communities. This makes data available that would not have been available otherwise. However, it is possible to collect a large amount of data that is unrelated to the research purpose. It's also feasible to utilise social media to promote market research possibilities and, as a result, to establish a community.

Researchers can tailor audiences and questions in online forums. Online communities also increase participant involvement, implying that researchers have their own sample bias, as well as the sample bias of individuals wanting to participate.

It is certainly possible to mine data from both systems. However, this method generates a lot of data to evaluate and a lot of variables to consider. Depending on how much data is needed, it might be worth it.

Both social media and online communities have advantages and disadvantages, and which platform to employ mostly depends on your marketing needs. However, I believe it would be a mistake to choose one and ignore the other because they are both extremely useful sources of information in their own right. While one platform may provide greater benefits for your marketing needs, mining both platforms will provide you with a comprehensive set of data.