{"version":"1.0","provider_name":"Institute for Data Science","provider_url":"https:\/\/carleton.ca\/cuids","author_name":"cuthemeedtr5","author_url":"https:\/\/carleton.ca\/cuids\/author\/cuthemeedtr5\/","title":"Aspect-based Sentiment Analysis and its Applications - Institute for Data Science","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"xd0HhxLZKB\"><a href=\"https:\/\/carleton.ca\/cuids\/event\/aspect-based-sentiment-analysis-and-its-applications\/\">Aspect-based Sentiment Analysis and its Applications<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/carleton.ca\/cuids\/event\/aspect-based-sentiment-analysis-and-its-applications\/embed\/#?secret=xd0HhxLZKB\" width=\"600\" height=\"338\" title=\"&#8220;Aspect-based Sentiment Analysis and its Applications&#8221; &#8212; Institute for Data Science\" data-secret=\"xd0HhxLZKB\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/carleton.ca\/cuids\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","description":"Abstract: Aspect-based sentiment analysis (ABSA) has recently attracted increasing research attention. Most previous work relies on syntax, such as automatic parse trees, which are subject to noise for informal text such as tweets and social media. In this project, we show that competitive results can be achieved without the use of syntax, by extracting a [&hellip;]"}