{"id":22,"date":"2015-10-30T14:07:37","date_gmt":"2015-10-30T14:07:37","guid":{"rendered":"http:\/\/blog.geneea.com\/?p=22"},"modified":"2026-01-29T21:24:19","modified_gmt":"2026-01-29T21:24:19","slug":"quick-analysis-of-sentiment-in-google-sheets","status":"publish","type":"post","link":"https:\/\/geneea.com\/news\/quick-analysis-of-sentiment-in-google-sheets","title":{"rendered":"Quick Analysis of Sentiment in Google Sheets"},"content":{"rendered":"

Having customer support messages, tweets, or Facebook comments all in one table is helpful. There is no doubt about that. However, what\u2019s even more useful is the ability to search the texts quickly for emotionally tinged mentions of your company.
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Even though everybody prefers reading positive reactions and reviews, it\u2019s the negative ones that help us grow the most<\/strong>. Using Google Sheets along with Geneea\u2019s text analytics<\/strong><\/a>, you can achieve this within a few minutes<\/strong>. Learn more about it in a short illustrative video below.<\/p>\n

Geneea\u2019s Interpretor REST API<\/a><\/strong> makes the connection with Google Sheets really easy. It has a whole series of functions available, such as text categorization, location, and people identification. (In case you attended this year\u2019s WebExpo<\/a><\/strong>, you might have seen our analysis of Svejk<\/a><\/strong> \u2013 available in Czech only; slides in English here<\/strong><\/a>).<\/p>\n

As a demonstration, we have prepared a few emotionally charged sentences and created a function that calls Geneea\u2019s API<\/strong>. Apply for your own API key here<\/strong><\/a>.\u00a0We need a simple Google Apps Script; something like this:<\/p>\n

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function <\/span>geneeaSentiment(text<\/span>) {    \n    var<\/span> userkey<\/span> = '<fill_your_api_key>'<\/span>    \n    var<\/span> url<\/span> = 'https:\/\/api.geneea.com:443\/s1\/sentiment?text='<\/span>         \n       + encodeURIComponent(text<\/span>) + '&&user_key='<\/span> + userkey<\/span>;    \n    var<\/span> response<\/span> = UrlFetchApp.fetch(url<\/span>);    \n    var<\/span> json<\/span> = response.getContentText();    \n    var<\/span> data<\/span> = JSON.parse(json<\/span>);    \n\n    return<\/span> data<\/span>.sentiment;\n}<\/span><\/pre>\n<\/blockquote>\n
Replace in the code with the API key you have received.<\/p>\n
Let\u2019s use our new function =geneeaSentiment(A2) in the spreadsheet. We can see that the majority of detected sentiment cases correspond to our own assessment<\/strong>. If you have thousands of such texts waiting for your attention, this will save a great deal of your time.<\/strong> Gone is the manual search for the most upset or the most pleased comments.<\/p>\n
All necessary steps are reviewed in the following minute-long video<\/strong>:<\/p>\n