![]() ![]() If you create or receive social listening reports that don't go beyond a word cloud, think about the additional analysis you could do to create insights. While you may see word clouds in our reports, they'll never be the center of attention. This requires analysis to identify insights. We believe that reports from social listening should be actionable, not just informative. Of course, we also love to share word clouds of conferences we attend. She started with a word cloud, but had to add additional structure to the data to complete an analysis that produced insights. Word clouds combined with trending data can help identify topics that are fading or emerging to inform your engagement or crisis response strategy.Īmber, a Campus Sonar analyst, detailed how she dove deep into a data set of 800,000 conversations about dropping out of college in a recent Brain Waves post. They're good to search for glaringly obvious differences in conversation between two audiences (e.g., a campus's owned conversation compared to their earned conversation, or your campus's online conversation compared to a competitor's). We use them all the time! They're good to look for irrelevant conversation (we use it regularly to clean data). Great Uses for Word Cloudsĭon't think we're word cloud haters. This is why Campus Sonar analysts are one of our greatest assets-in-depth online conversation analysis requires a human understanding of a data set in order to provide the structure appropriate to the questions you're looking to the data to answer. By coding conversation data, we can look at the conversations about the community feeling expressed by many HighEdWeb attendees by coding mentions of "my people," "friends," "community," "they get me," etc., as "sense of belonging." Other mentions of "data is the new fuel" and "keynote" can be combined with other references to Tatjana Dzambazova's mind-blowing keynote and coded as such. It gets beyond word clouds and provides a structure to data analysis. This is an extremely useful methodology to use to compare online conversation. Qualitative researchers are familiar with coding their data around themes. Moving Beyond Word Clouds for Conversation Analysis ![]() Proximity of words or phrases in the word cloud to each other, for example, has no significant meaning. Sometimes the cloud will be coded for sentiment (green = positive, red = negative, gray = neutral). The more a word or phrase appears in a data set, the larger it's displayed on the word cloud. Here's a word cloud from the online conversation about the 2017 AMA Higher Education conference and the corresponding data table. The frequency of each word or phrase in a data set is counted to create the word cloud. In fact, there is a data table that powers every word cloud. Word clouds are a quantitative representation of qualitative data. ![]()
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