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Social Listening vs Social Monitoring: What’s The Difference?

Social monitoring is the practice of companies looking at their social profiles on Twitter, Facebook, Instagram, etc.

Unfortunately, when companies engage in social monitoring, they don’t have the proper lens to obtain the bigger picture they are seeking. This lack of vision is because they only view mentions on their particular sites or channels. Often the insight they seek occurs off their social media sites and resides in conversations happening in other social media forums. As a result, companies looking at their social media could get a false sense of security that everything is okay because they’re not looking at all the other areas where opinions are being shared and spread.

Social monitoring sometimes masks the truth because it focuses on the company’s specific channels and misses its competitors. This type of conversation occurs everywhere online regarding food, beverage, pharmaceutical, and consumer goods. People often engage in free-flowing, organic conversations that are more accurate expressions of their true thoughts. The “true” consumer expression evades the traditional survey market research method and is often absent from social monitoring.

Social Listening

Social listening collects and derives insights from all social mentions no matter where they occur online. It uses sophisticated linguistic modeling to locate relevant comments and conversations appearing anywhere on social media – Twitter, Facebook, Instagram, Tumblr, TikTok, etc., to analyze a rich social media data set. Social listening provides a transparent and objective resource to examine conversation topics, sentiment, and any other category of interest.

Crisis management or reputation management is an excellent example of social listening. Companies seeking to guard against public relations risk and threats want to intercept and mitigate any negative mentions before they have a chance to go viral.

Expert analysts bring significant experience and analytical expertise to recognize signals present in social media noise. Of course, when or why something goes viral is challenging to predict, but Social Listening has to be part of the equation.

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AI Is Not Ready For Sentiment Analysis

Sentiment analysis determines how much of the conversation is positive, negative, or neutral. Currently, much sentiment analysis relies on Artificial Intelligence (AI) to assign sentiment to posts using one-size-fits-all algorithms.

But AI is only so intelligent. When it comes to social media posts, people are sarcastic, making jokes, or using slang. For example, the word “sick” has a reasonably direct definition; however, the same word used as a slang term means its direct opposite. For example, consider “that snowboard is sick, dude!”

Social listening will categorize this post as positive. However, AI will analyze this post as a negative occurrence.

Similarly, when comparing products or brands, it’s not unusual for consumers to offer contrasting opinions within the same mention.

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A mention with favorable terms towards Coca-Cola and negative words towards Pepsi would likely confuse AI because it doesn’t consider the context. The sentiment of that post depends entirely upon whether your client is Coke or Pepsi.

Relying entirely on AI for this segmentation is a bit disastrous. Once you start digging deeper into this type of automatic categorization, you often find that it’s just incorrect. For example, AI will not reveal why the mention is negative or positive, but social listening will.

Social Listening Process

There are many ways to normalize the collected social listening metrics across different platforms. For example, follower count, reach, and impressions are standard metrics across all social monitoring. Content-type, post frequency/recency, and author qualifications/influence are data that must be normalized to provide a more holistic understanding of the broader social landscape for a given brand, product, or industry.

Looking deeply into who a particular follower is provides unique insights into the relevance of their content. Who are their followers? Is the author an educator or a potential brand ambassador? Or, can you dismiss the ravings of an anonymous person with a negative opinion? Social listening takes all this into account to evaluate whether any given mention has merit, or can be dismissed. In addition, knowing where to look and the value of that particular social media platform must be taken into account—because each holds different values. For example:

  • Instagram and TikTok are sites where users post visual, and/or video content, which is effective at grabbing followers’ attention.
  • Reddit is an anonymous forum site, which allows users to feel comfortable discussing sometimes difficult and personal topics.
  • Twitter is a site where much sharing occurs in the form of Retweets but is also a good indicator of whether something has reached “viral” status.
  • Facebook still has a huge number of users and while engagement might be low it’s understood that there is a significant number of “lurkers” on Facebook, which can broaden reach and impressions.
  • Tumblr is closer to a personal diary than a real social network, however, it allows users to give in-depth details about opinions, and experiences. Pinterest is low engagement, but it provides valuable information on lifestyle trends and changes and insights on food, diet, and exercise.

Beware Of The Multi-Agency Noise

Companies often hire many different agencies to create content, copy and place ads. Companies may have a separate media placement agency that distributes ads, another agency to create the ad strategy, and an additional agency tasked with promoting the content on social media. Using multiple agencies in this fashion could result in siloed reports on each, individual contribution, making it difficult to determine a clear understanding of how social strategy is functioning. Social Listening, particularly from a third-party agency could provide an objective evaluation that gives brand teams a bird’s-eye view of content performance.

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Another advantage of social listening is that obtaining results can be achieved quickly.

Linguistic models can be quickly developed and easily deployed to begin collecting social posts immediately. Many social platforms allow for up to ten years of data retrieval, ensuring that long-term studies are just as viable as up-to-the-minute, real-time reporting. Unlike traditional market research methods, which can take a long time to develop, deploy, and derive insights from, social listening can have a complete dashboard view of the data in just a matter of hours. The process is highly customizable and can turn on a dime to change methodology or update linguistic models instantly. The speed of social listening is a great asset that is often overlooked.

Data derived from social listening is a rich source of information and insights which can be tapped by skilled analysts, who are experts in social media, linguistics, and research methodologies.

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