When the editor of a text-mining tool tells you that conversational data* is not suitable for the use of his solution, you are suddenly thrown back to the basic principle of data analysis: garbage in, garbage out<\/strong>.<\/p>\n\n\n\n Eternally frustrated by the segmentation features<\/strong> of all the monitoring tools and always in search of new solutions, I went back in search of a coding tool<\/strong>. Attending a demonstration of Codei<\/a>t<\/a>I was struck by the precision with which the tool identifies the opinion markers<\/strong> in the clients' verbatim.<\/p>\n\n\n\n Admittedly, it was a \"demo\", but the ease with which the corpus is codified, in a fluid loop between machine and human, made me dream again. Tracking opinion<\/strong> into the intricacies of the web and discover its mechanisms, wasn't that the reason I got into this field 15 years ago?<\/p>\n\n\n\n Overcome serendipity and its best friend, intuition, by conducting solid research based on a quality body of work and a proven methodology. Listen to the opinions of people who will never be on the radio or television and who will never publish an article or even a customer review on Google Maps. Identify the issues and concerns of citizens and consumers before they are editorialized.<\/p>\n\n\n\n This was the course<\/strong>. It remains mine today, as it is for so many other professionals claiming to be in the business of monitoring and analysis for marketing and communication. Nevertheless, I fear that the hyper-presence of brands and other communication actors on social networks and even social networks (Trump, Elon,...) hide a certain information poverty<\/strong>.<\/p>\n\n\n It is still assumed that there will be enough mentions of this or that brand to produce a competitive analysis when the corpus is infested with spam, homonyms or simple promotional messages.<\/p>\n\n\n\n Before refiltering and despite the precision of the collection requests, I find waste rate easily exceeding 50%<\/strong> in some cases. Who has not found the name of an athlete or a sports club (football, basketball, baseball, etc.) in their corpus by performing a quality control before proceeding with the analysis? Who dares to say it and who is there to hear it?<\/strong><\/p>\n\n\n\n Let us not believe that theautomatic learning<\/strong> and theartificial intelligence<\/strong> will solve this fundamental problem. On the contrary, this situation makes the exploitation of these new technologies impossible. The (aborted) experiment of this product demonstration proves this.<\/p>\n\n\n\n I still dream of a coding tool like Codeit integrated into a monitoring solution. I dream just as much about the quality data that I find here and there, never tired of actively searching for it.<\/p>\n\n\n\n PS: Codeit has been designed to code survey data (polls) and consumer opinions. You can use it test online<\/a>. This solution would have been very useful to me, some time ago, in the analysis of internal surveys (internal communication, change management, etc.). And no, I am not being paid to write this article.<\/p>\n\n\n\n *publications from forums, social networks and messaging services.<\/em><\/p>\n\n\n\n Photo by Greg Rakozy<\/a> on Unsplash<\/a><\/em><\/p>","protected":false},"excerpt":{"rendered":" Reading Time: <\/span> 2<\/span> minutes<\/span><\/span> When the editor of a text-mining tool tells you that conversational data* does not lend itself to the use of its solution, you are suddenly thrown back to the basic principle of data analysis: garbage in, garbage out. Eternally frustrated by the segmentation features of all the monitoring and analysis tools available, you ...<\/p>","protected":false},"author":1,"featured_media":1916,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[50],"tags":[],"class_list":["post-1905","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-nouveautes"],"acf":[],"_links":{"self":[{"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/posts\/1905","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/comments?post=1905"}],"version-history":[{"count":10,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/posts\/1905\/revisions"}],"predecessor-version":[{"id":1928,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/posts\/1905\/revisions\/1928"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/media\/1916"}],"wp:attachment":[{"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/media?parent=1905"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/categories?post=1905"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/avhmag.com\/en\/wp-json\/wp\/v2\/tags?post=1905"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"Photo](\"http:\/\/avhmag.com\/wp-content\/uploads\/2022\/11\/greg-rakozy-oMpAz-DN-9I-unsplash.jpg\")