{"id":478923,"date":"2023-08-09T09:40:29","date_gmt":"2023-08-09T09:40:29","guid":{"rendered":""},"modified":"2023-09-05T11:17:48","modified_gmt":"2023-09-05T11:17:48","slug":"sentiment-analysis","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/sentiment-analysis\/","title":{"rendered":"Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m"},"content":{"rendered":"<p>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m, c\u00f2n \u0111\u01b0\u1ee3c g\u1ecdi l\u00e0 khai th\u00e1c \u00fd ki\u1ebfn ho\u1eb7c AI c\u1ea3m x\u00fac, \u0111\u1ec1 c\u1eadp \u0111\u1ebfn vi\u1ec7c s\u1eed d\u1ee5ng x\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean (NLP), ph\u00e2n t\u00edch v\u0103n b\u1ea3n v\u00e0 ng\u00f4n ng\u1eef h\u1ecdc t\u00ednh to\u00e1n \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh v\u00e0 tr\u00edch xu\u1ea5t th\u00f4ng tin ch\u1ee7 quan t\u1eeb t\u00e0i li\u1ec7u ngu\u1ed3n. V\u1ec1 c\u01a1 b\u1ea3n, n\u00f3 x\u00e1c \u0111\u1ecbnh th\u00e1i \u0111\u1ed9 ho\u1eb7c c\u1ea3m x\u00fac \u0111\u01b0\u1ee3c truy\u1ec1n t\u1ea3i trong m\u1ed9t chu\u1ed7i t\u1eeb, \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong c\u00e1c cu\u1ed9c tr\u00f2 chuy\u1ec7n ho\u1eb7c v\u0103n b\u1ea3n tr\u1ef1c tuy\u1ebfn, \u0111\u1ed1i v\u1edbi c\u00e1c ch\u1ee7 \u0111\u1ec1 ho\u1eb7c s\u1ea3n ph\u1ea9m nh\u1ea5t \u0111\u1ecbnh.<\/p>\n<h2>L\u1ecbch s\u1eed ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<p>L\u1ecbch s\u1eed c\u1ee7a ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m c\u00f3 th\u1ec3 b\u1eaft ngu\u1ed3n t\u1eeb \u0111\u1ea7u nh\u1eefng n\u0103m 2000 khi s\u1ef1 ph\u00e1t tri\u1ec3n nhanh ch\u00f3ng c\u1ee7a n\u1ed9i dung tr\u1ef1c tuy\u1ebfn \u0111\u00e3 th\u00fac \u0111\u1ea9y s\u1ef1 quan t\u00e2m \u0111\u1ebfn c\u00e1c k\u1ef9 thu\u1eadt t\u1ef1 \u0111\u1ed9ng \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh \u00fd ki\u1ebfn v\u00e0 c\u1ea3m x\u00fac trong v\u0103n b\u1ea3n. L\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u1ec1 c\u1eadp \u0111\u1ebfn n\u00f3 l\u00e0 s\u1ef1 ra \u0111\u1eddi c\u1ee7a Web 2.0, n\u01a1i n\u1ed9i dung do ng\u01b0\u1eddi ti\u00eau d\u00f9ng t\u1ea1o ra b\u1eaft \u0111\u1ea7u th\u1ed1ng tr\u1ecb b\u1ed1i c\u1ea3nh internet.<\/p>\n<p>Thu\u1eadt ng\u1eef \u201cph\u00e2n t\u00edch t\u00ecnh c\u1ea3m\u201d b\u1eaft \u0111\u1ea7u xu\u1ea5t hi\u1ec7n trong c\u00e1c t\u00e0i li\u1ec7u nghi\u00ean c\u1ee9u, v\u1edbi c\u00f4ng tr\u00ecnh nghi\u00ean c\u1ee9u s\u00e2u r\u1ed9ng c\u1ee7a c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u nh\u01b0 Bo Pang v\u00e0 Lillian Lee v\u00e0o n\u0103m 2002, \u0111\u00e1nh d\u1ea5u s\u1ef1 kh\u1edfi \u0111\u1ea7u c\u1ee7a ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m nh\u01b0 m\u1ed9t l\u0129nh v\u1ef1c ri\u00eang bi\u1ec7t trong ng\u00f4n ng\u1eef h\u1ecdc t\u00ednh to\u00e1n.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<p>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m bao g\u1ed3m nhi\u1ec1u ph\u01b0\u01a1ng ph\u00e1p v\u00e0 k\u1ef9 thu\u1eadt kh\u00e1c nhau \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 di\u1ec5n gi\u1ea3i v\u00e0 ph\u00e2n lo\u1ea1i c\u1ea3m x\u00fac trong d\u1eef li\u1ec7u v\u0103n b\u1ea3n. N\u00f3 c\u00f3 th\u1ec3 ph\u00e2n t\u00edch n\u1ed9i dung do ng\u01b0\u1eddi d\u00f9ng t\u1ea1o nh\u01b0 \u0111\u00e1nh gi\u00e1, tweet, nh\u1eadn x\u00e9t ho\u1eb7c b\u1ea5t k\u1ef3 n\u1ed9i dung v\u0103n b\u1ea3n n\u00e0o c\u00f3 th\u1ec3 ch\u1ee9a \u00fd ki\u1ebfn ch\u1ee7 quan.<\/p>\n<h3>C\u1ea5p \u0111\u1ed9 ph\u00e2n t\u00edch<\/h3>\n<ul>\n<li><strong>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m \u1edf c\u1ea5p \u0111\u1ed9 t\u00e0i li\u1ec7u:<\/strong> Ph\u00e2n t\u00edch to\u00e0n b\u1ed9 t\u00e0i li\u1ec7u ho\u1eb7c v\u0103n b\u1ea3n.<\/li>\n<li><strong>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m \u1edf c\u1ea5p \u0111\u1ed9 c\u00e2u:<\/strong> Ph\u00e2n t\u00edch t\u1eebng c\u00e2u m\u1ed9t.<\/li>\n<li><strong>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m \u1edf c\u1ea5p \u0111\u1ed9 kh\u00eda c\u1ea1nh:<\/strong> T\u1eadp trung v\u00e0o c\u00e1c kh\u00eda c\u1ea1nh ho\u1eb7c t\u00ednh n\u0103ng c\u1ee5 th\u1ec3 c\u1ee7a s\u1ea3n ph\u1ea9m ho\u1eb7c ch\u1ee7 \u0111\u1ec1.<\/li>\n<\/ul>\n<h3>K\u1ef9 thu\u1eadt \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng<\/h3>\n<ul>\n<li><strong>Ph\u01b0\u01a1ng ph\u00e1p h\u1ecdc m\u00e1y:<\/strong> S\u1eed d\u1ee5ng c\u00e1c thu\u1eadt to\u00e1n nh\u01b0 SVM, Naive Bayes, Random Forests, v.v.<\/li>\n<li><strong>Ph\u01b0\u01a1ng ph\u00e1p d\u1ef1a tr\u00ean t\u1eeb \u0111i\u1ec3n:<\/strong> S\u1eed d\u1ee5ng danh s\u00e1ch c\u00e1c t\u1eeb \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc v\u00e0 \u0111i\u1ec3m t\u00ecnh c\u1ea3m c\u1ee7a ch\u00fang.<\/li>\n<li><strong>Ph\u01b0\u01a1ng ph\u00e1p lai:<\/strong> K\u1ebft h\u1ee3p c\u00e1c k\u1ef9 thu\u1eadt h\u1ecdc m\u00e1y v\u00e0 d\u1ef1a tr\u00ean t\u1eeb v\u1ef1ng.<\/li>\n<\/ul>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<p>Ho\u1ea1t \u0111\u1ed9ng n\u1ed9i b\u1ed9 c\u1ee7a ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c chia th\u00e0nh c\u00e1c b\u01b0\u1edbc sau:<\/p>\n<ol>\n<li><strong>Ti\u1ec1n x\u1eed l\u00fd v\u0103n b\u1ea3n:<\/strong> Lo\u1ea1i b\u1ecf c\u00e1c k\u00fd hi\u1ec7u kh\u00f4ng c\u1ea7n thi\u1ebft, g\u1ed1c, m\u00e3 th\u00f4ng b\u00e1o, v.v.<\/li>\n<li><strong>Khai th\u00e1c t\u00ednh n\u0103ng:<\/strong> Tr\u00edch xu\u1ea5t c\u00e1c t\u1eeb v\u00e0 c\u1ee5m t\u1eeb ch\u00ednh c\u00f3 th\u1ec3 bi\u1ec3u th\u1ecb t\u00ecnh c\u1ea3m.<\/li>\n<li><strong>\u0110\u00e0o t\u1ea1o &amp; ph\u00e2n lo\u1ea1i m\u00f4 h\u00ecnh:<\/strong> S\u1eed d\u1ee5ng thu\u1eadt to\u00e1n ML \u0111\u1ec3 \u0111\u00e0o t\u1ea1o m\u00f4 h\u00ecnh v\u00e0 ph\u00e2n lo\u1ea1i c\u1ea3m t\u00ednh.<\/li>\n<li><strong>Ch\u1ea5m \u0111i\u1ec3m t\u00ecnh c\u1ea3m:<\/strong> Ch\u1ec9 \u0111\u1ecbnh \u0111i\u1ec3m t\u00ecnh c\u1ea3m (t\u00edch c\u1ef1c, ti\u00eau c\u1ef1c ho\u1eb7c trung t\u00ednh).<\/li>\n<\/ol>\n<h2>Ph\u00e2n t\u00edch c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh c\u1ee7a ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<ul>\n<li><strong>S\u1ef1 ch\u00ednh x\u00e1c:<\/strong> \u0110\u1ed9 ch\u00ednh x\u00e1c m\u00e0 c\u1ea3m x\u00fac \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n.<\/li>\n<li><strong>Ph\u00e2n t\u00edch th\u1eddi gian th\u1ef1c:<\/strong> Kh\u1ea3 n\u0103ng ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m trong th\u1eddi gian th\u1ef1c, \u0111\u1eb7c bi\u1ec7t l\u00e0 tr\u00ean m\u1ea1ng x\u00e3 h\u1ed9i.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng:<\/strong> X\u1eed l\u00fd l\u01b0\u1ee3ng l\u1edbn d\u1eef li\u1ec7u m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3.<\/li>\n<li><strong>H\u1ed7 tr\u1ee3 ng\u00f4n ng\u1eef:<\/strong> Kh\u1ea3 n\u0103ng hi\u1ec3u c\u00e1c ng\u00f4n ng\u1eef v\u00e0 ph\u01b0\u01a1ng ng\u1eef kh\u00e1c nhau.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng th\u00edch \u1ee9ng:<\/strong> Th\u00edch \u1ee9ng v\u1edbi nhi\u1ec1u l\u0129nh v\u1ef1c v\u00e0 b\u1ed1i c\u1ea3nh kh\u00e1c nhau.<\/li>\n<\/ul>\n<h2>C\u00e1c lo\u1ea1i ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<p>D\u01b0\u1edbi \u0111\u00e2y l\u00e0 c\u00e1c lo\u1ea1i ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m ch\u00ednh:<\/p>\n<table>\n<thead>\n<tr>\n<th>Ki\u1ec3u<\/th>\n<th>S\u1ef1 mi\u00eau t\u1ea3<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>H\u1ea1t m\u1ecbn<\/td>\n<td>Ph\u00e2n bi\u1ec7t c\u00e1c m\u1ee9c \u0111\u1ed9 t\u00edch c\u1ef1c\/ti\u00eau c\u1ef1c kh\u00e1c nhau.<\/td>\n<\/tr>\n<tr>\n<td>Ph\u00e1t hi\u1ec7n c\u1ea3m x\u00fac<\/td>\n<td>X\u00e1c \u0111\u1ecbnh nh\u1eefng c\u1ea3m x\u00fac c\u1ee5 th\u1ec3 nh\u01b0 vui, gi\u1eadn, bu\u1ed3n, v.v.<\/td>\n<\/tr>\n<tr>\n<td>D\u1ef1a tr\u00ean kh\u00eda c\u1ea1nh<\/td>\n<td>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m \u0111\u1ed1i v\u1edbi c\u00e1c kh\u00eda c\u1ea1nh ho\u1eb7c t\u00ednh n\u0103ng c\u1ee5 th\u1ec3.<\/td>\n<\/tr>\n<tr>\n<td>Ph\u00e2n t\u00edch \u00fd \u0111\u1ecbnh<\/td>\n<td>X\u00e1c \u0111\u1ecbnh \u00fd \u0111\u1ecbnh \u0111\u1eb1ng sau t\u00ecnh c\u1ea3m, ch\u1eb3ng h\u1ea1n nh\u01b0 \u00fd \u0111\u1ecbnh mua h\u00e0ng.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m, v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p<\/h2>\n<h3>C\u00e1ch s\u1eed d\u1ee5ng<\/h3>\n<ul>\n<li><strong>Gi\u00e1m s\u00e1t ti\u1ebfp th\u1ecb &amp; th\u01b0\u01a1ng hi\u1ec7u:<\/strong> Th\u1ea5u hi\u1ec3u \u00fd ki\u1ebfn kh\u00e1ch h\u00e0ng.<\/li>\n<li><strong>H\u1ed7 tr\u1ee3 kh\u00e1ch h\u00e0ng:<\/strong> T\u0103ng c\u01b0\u1eddng h\u1ed7 tr\u1ee3 th\u00f4ng qua s\u1ef1 hi\u1ec3u bi\u1ebft t\u00ecnh c\u1ea3m.<\/li>\n<li><strong>Ph\u00e2n t\u00edch s\u1ea3n ph\u1ea9m:<\/strong> \u0110\u00e1nh gi\u00e1 vi\u1ec7c ti\u1ebfp nh\u1eadn v\u00e0 ph\u1ea3n h\u1ed3i s\u1ea3n ph\u1ea9m.<\/li>\n<\/ul>\n<h3>C\u00e1c v\u1ea5n \u0111\u1ec1<\/h3>\n<ul>\n<li><strong>S\u1ef1 m\u1ec9a mai &amp; m\u01a1 h\u1ed3:<\/strong> Kh\u00f3 kh\u0103n trong vi\u1ec7c ph\u00e1t hi\u1ec7n t\u00ecnh c\u1ea3m th\u1ef1c s\u1ef1.<\/li>\n<li><strong>Nh\u1eefng th\u00e1ch th\u1ee9c \u0111a ng\u00f4n ng\u1eef:<\/strong> H\u1ed7 tr\u1ee3 h\u1ea1n ch\u1ebf cho nhi\u1ec1u ng\u00f4n ng\u1eef kh\u00e1c nhau.<\/li>\n<\/ul>\n<h3>C\u00e1c gi\u1ea3i ph\u00e1p<\/h3>\n<ul>\n<li><strong>Thu\u1eadt to\u00e1n n\u00e2ng cao:<\/strong> Tri\u1ec3n khai c\u00e1c m\u00f4 h\u00ecnh ph\u1ee9c t\u1ea1p h\u01a1n.<\/li>\n<li><strong>B\u1ed1i c\u1ea3nh k\u1ebft h\u1ee3p:<\/strong> Hi\u1ec3u b\u1ed1i c\u1ea3nh r\u1ed9ng h\u01a1n \u0111\u1ec3 gi\u1ea3i th\u00edch t\u00ecnh c\u1ea3m.<\/li>\n<\/ul>\n<h2>\u0110\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 so s\u00e1nh<\/h2>\n<h3>\u0110\u1eb7c tr\u01b0ng<\/h3>\n<ul>\n<li><strong>T\u00ednh linh ho\u1ea1t:<\/strong> \u00c1p d\u1ee5ng tr\u00ean nhi\u1ec1u ng\u00e0nh v\u00e0 l\u0129nh v\u1ef1c kh\u00e1c nhau.<\/li>\n<li><strong>\u0110\u1ed9 ph\u1ee9c t\u1ea1p:<\/strong> M\u1ee9c \u0111\u1ed9 ph\u1ee9c t\u1ea1p kh\u00e1c nhau t\u00f9y thu\u1ed9c v\u00e0o k\u1ef9 thu\u1eadt \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng \u1ee9ng d\u1ee5ng th\u1eddi gian th\u1ef1c:<\/strong> Kh\u1ea3 n\u0103ng ph\u00e2n t\u00edch lu\u1ed3ng d\u1eef li\u1ec7u tr\u1ef1c ti\u1ebfp.<\/li>\n<\/ul>\n<h3>So s\u00e1nh<\/h3>\n<p>So s\u00e1nh ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m v\u1edbi c\u00e1c thu\u1eadt ng\u1eef t\u01b0\u01a1ng t\u1ef1 kh\u00e1c:<\/p>\n<table>\n<thead>\n<tr>\n<th>Thu\u1eadt ng\u1eef<\/th>\n<th>Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/th>\n<th>\u0110i\u1ec1u kho\u1ea3n li\u00ean quan<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Kh\u00e1ch quan<\/td>\n<td>Ph\u00e1t hi\u1ec7n \u00fd ki\u1ebfn ch\u1ee7 quan<\/td>\n<td>Khai th\u00e1c th\u00f4ng tin th\u1ef1c t\u1ebf<\/td>\n<\/tr>\n<tr>\n<td>K\u1ef9 thu\u1eadt<\/td>\n<td>ML, d\u1ef1a tr\u00ean Lexicon, K\u1ebft h\u1ee3p<\/td>\n<td>D\u1ef1a tr\u00ean quy t\u1eafc, \u0111\u1ed1i s\u00e1nh t\u1eeb kh\u00f3a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 c\u1ee7a t\u01b0\u01a1ng lai li\u00ean quan \u0111\u1ebfn ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<ul>\n<li><strong>T\u00edch h\u1ee3p v\u1edbi IoT:<\/strong> Ph\u00e2n t\u00edch c\u1ea3m x\u00fac theo th\u1eddi gian th\u1ef1c v\u1ec1 gi\u1ecdng n\u00f3i v\u00e0 n\u00e9t m\u1eb7t.<\/li>\n<li><strong>C\u00e1c m\u00f4 h\u00ecnh AI n\u00e2ng cao:<\/strong> H\u1ecdc s\u00e2u \u0111\u1ec3 hi\u1ec3u r\u00f5 h\u01a1n.<\/li>\n<li><strong>Ph\u00e2n t\u00edch \u0111a ng\u00f4n ng\u1eef:<\/strong> Ph\u00e1 v\u1ee1 r\u00e0o c\u1ea3n ng\u00f4n ng\u1eef.<\/li>\n<\/ul>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m<\/h2>\n<p>C\u00e1c m\u00e1y ch\u1ee7 proxy nh\u01b0 OneProxy c\u00f3 th\u1ec3 \u0111\u00f3ng m\u1ed9t vai tr\u00f2 quan tr\u1ecdng trong ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m b\u1eb1ng c\u00e1ch:<\/p>\n<ul>\n<li><strong>Qu\u00e9t d\u1eef li\u1ec7u:<\/strong> Thu th\u1eadp d\u1eef li\u1ec7u t\u1eeb nhi\u1ec1u ngu\u1ed3n tr\u1ef1c tuy\u1ebfn m\u1ed9t c\u00e1ch an to\u00e0n.<\/li>\n<li><strong>\u1ea8n danh &amp; B\u1ea3o m\u1eadt:<\/strong> \u0110\u1ea3m b\u1ea3o thu th\u1eadp d\u1eef li\u1ec7u \u1ea9n danh.<\/li>\n<li><strong>Ki\u1ec3m tra v\u1ecb tr\u00ed \u0111\u1ecba l\u00fd:<\/strong> Ph\u00e2n t\u00edch t\u00ecnh c\u1ea3m gi\u1eefa c\u00e1c khu v\u1ef1c kh\u00e1c nhau.<\/li>\n<\/ul>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">Trang web OneProxy<\/a><\/li>\n<li><a href=\"http:\/\/nlp.stanford.edu\/\" target=\"_new\" rel=\"noopener nofollow\">Nh\u00f3m NLP Stanford<\/a><\/li>\n<li><a href=\"https:\/\/www.nltk.org\/\" target=\"_new\" rel=\"noopener nofollow\">B\u1ed9 c\u00f4ng c\u1ee5 ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean (NLTK)<\/a><\/li>\n<li><a href=\"http:\/\/www.cs.cornell.edu\/home\/llee\/omsa\/omsa.pdf\" target=\"_new\" rel=\"noopener nofollow\">Nghi\u00ean c\u1ee9u c\u1ee7a Bo Pang v\u00e0 Lillian Lee<\/a><\/li>\n<\/ul>","protected":false},"featured_media":470461,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478923","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Sentiment Analysis<\/mark>","faq_items":[{"question":"What is Sentiment Analysis?","answer":"<p>Sentiment Analysis, also known as opinion mining or emotion AI, is a field that uses natural language processing (NLP), text analysis, and computational linguistics to identify and extract subjective information from text. It determines the emotions or attitudes conveyed towards certain topics or products.<\/p>"},{"question":"What is the history of Sentiment Analysis?","answer":"<p>The history of sentiment analysis dates back to the early 2000s with the rise of Web 2.0. Researchers like Bo Pang and Lillian Lee were instrumental in developing sentiment analysis as a distinct field within computational linguistics, beginning in 2002.<\/p>"},{"question":"How does Sentiment Analysis work?","answer":"<p>Sentiment Analysis works by first preprocessing the text to remove unnecessary symbols and extract key words or phrases. Then, it uses machine learning algorithms to train models and classify the sentiments into categories like positive, negative, or neutral. Finally, a sentiment score is assigned to the analyzed content.<\/p>"},{"question":"What are the key features of Sentiment Analysis?","answer":"<p>Key features of Sentiment Analysis include its accuracy, real-time analysis capabilities, scalability, language support, and adaptability to various domains and contexts.<\/p>"},{"question":"What types of Sentiment Analysis exist?","answer":"<p>There are several types of Sentiment Analysis including Fine-Grained, Emotion Detection, Aspect-Based, and Intent Analysis. These types allow for various levels of analysis, from understanding specific emotions to analyzing sentiments towards particular aspects or features.<\/p>"},{"question":"How can Sentiment Analysis be used and what problems may arise?","answer":"<p>Sentiment Analysis can be used in marketing, brand monitoring, customer support, and product analysis. Some problems that may arise include the detection of sarcasm and ambiguity, and limited support for multiple languages. These challenges can be addressed through advanced algorithms and understanding broader contexts.<\/p>"},{"question":"How is Sentiment Analysis evolving and what future technologies are expected?","answer":"<p>Sentiment Analysis is expected to integrate with IoT for real-time analysis of voice and facial expressions, develop enhanced AI models through deep learning, and break language barriers with cross-language analysis.<\/p>"},{"question":"How can proxy servers like OneProxy be associated with Sentiment Analysis?","answer":"<p>Proxy servers like OneProxy can be used in sentiment analysis to securely gather data from various online sources, ensure anonymous data collection, and enable the analysis of sentiments across different regions through geo-location testing.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478923","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478923\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/470461"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=478923"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}