The Authors Tab uncovers the 'who' behind the conversation. In addition to the list of influencers that the legacy Authors Tab surfaces, this experience uncovers the demographics, top professions, and interests of the people tweeting about the topics and companies most relevant to you.

The Authors Tab captures the key opinion leaders engaging in the conversation. Each Author profile card found on the left had side will include:

Add Authors to a list by either selecting all results or individually selecting authors based on your requirements. You can complete the step by clicking the ‘Add to list’ button. You’ll then be prompted to add the authors to an existing list or create a new one.

In a similar fashion, you can export the list of Authors as a CSV file. You’ll notice the export option by hovering over the ‘down arrow’ option.

Now let's breakdown each widget below:

The 'Unique Twitter Authors' widget represents the number of authors who have tweeted at least once about the term found in your search. If, for example, one author tweets five separate times while incorporating your search term(s), that author will be counted just once against the total number of unique authors.

Twitter Verification represents a percentage breakdown of the authors tweeting about your search term who are verified versus not verified. Verified users tend to represent authors with a large following and strong influence. In effect, this figure shows you how much of the conversation is dominated by key opinion leaders versus everyday, normal Twitter users.

The gender breakdown estimates the split between male and female authors. The gender of authors is inferred through our ML-based models that look at data like name, screen name and profile description.

The age breakdown segments authors by age categories. The age categories are 13 to 17, 18 to 24, 25 to 34, 35 to 44, 45 to 54, 55-64, and 65+. The age of an author is determined by our ML-models as well, looking at a combination of declarative data and inferred data from the user's profile.

Top Author Location shows you where the authors are physically located or tweeting when they tweet about your search terms.

The top professions represent the most common occupations of the authors tweeting about your search term. Meltwater generates this information by analyzing and finding any professional terms found within the Twitter user's profile. If your audience includes researchers or academics, you'll know to heighten the sophistication and seriousness of your language. If, when running a search on 'cats', you find a contingent of authors identify as 'rescuers', you'll know to channel this passion and empathy in your messaging.

Using the public information declared by each user across their profiles, we can run a keyword cloud visualization to show the relative frequency of terms. This will help you find patterns in how your audience thinks, describes, or identifies themselves to the rest of the world. Again, you can use this information and mirror it across your copy, CTAs, and ad-creative.

Of course, audiences don't think of themselves just in terms of their age, race, and jobs. Especially today's digital consumers, they like to think of themselves in terms of affinities, hobbies, and interests. When looking at their historical Tweets and Re-tweets, Meltwater can surface your audience's top interests. Interests can include Sports, Travel, Science, Movies and TV, and more. We generate these interests by looking at each author's timeline of tweets and re-tweets. Knowing this information can help you identify the unique and shared attributes of a particular audience, and again help you activate and engage in a more meaningful and familiar way. Knowing what you know about their interests, how can you better entertain, educate and inspire your audience?

Lastly, Meltwater will show you the top languages of the authors tweeting about the topic found in your search terms. We generate the language breakdown by determining the predominant language used by the author across their tweets.

💡 Tip

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