Opinion mining on Indonesian tourism TikTok video content using fasttext and multilayer long short-term memory

Social media analysis is a trending topic among researchers, especially in exploring public opinion. The evolution of web 2.0 technology is a strong reason for turning social media into a digital platform that can easily facilitate various user expressions and opinions through diverse content. Expre...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Ariyus, Dony, Manongga, Danny, Sembiring, Irwan
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 1
container_start_page
container_title
container_volume 3077
creator Ariyus, Dony
Manongga, Danny
Sembiring, Irwan
description Social media analysis is a trending topic among researchers, especially in exploring public opinion. The evolution of web 2.0 technology is a strong reason for turning social media into a digital platform that can easily facilitate various user expressions and opinions through diverse content. Expressions and opinions that emerge through interaction between social media users have great potential to be studied and used in various contexts, including for the government, which aims to understand the thoughts of its citizens regarding newly implemented public policies. Recently, the Government of the Republic of Indonesia established five super-priority tourist destinations through the Ministry of Tourism and Creative Economy (Kemenparekraf) to increase foreign exchange through tourism. These destinations are Lake Toba, Labuan Bajo, Borobudur, Mandalika, and Likupang. However, the policies launched need to be analyzed to support the success of the launched policies. One way is to analyze public opinion to find out how many citizens will recommend the destination. TikTok, one of the most used social media platforms on the market, can be used to investigate public opinion about specific tourist locations. Nowadays, many young travelers use TikTok to express their thoughts and feelings. Due to the non-standard language and the frequent use of slang in daily interactions, extracting opinions on TikTok’s social media data presents specific difficulties. It might be beneficial to utilize a language corpus frequently used to analyze public sentiment more accurately. This study used FastText word embedding combined with the Long Short - Term Memory (LSTM) model with single, double, and triple layers to investigate the public’s opinion of Tiktok social media data. Based on the experiment, using FastText and LSTM with multiple layers provides good performance in developing various system innovations for investigating public opinion, especially on social media data TikTok.
doi_str_mv 10.1063/5.0202656
format Conference Proceeding
fullrecord <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_proquest_journals_3079464231</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3079464231</sourcerecordid><originalsourceid>FETCH-LOGICAL-p636-fff2e7a0379166c55add3de18a9a73b46a03b3f9d0bb8270a0234dd2f4ac5faa3</originalsourceid><addsrcrecordid>eNotkM1KAzEUhYMoWKsL3yDgTpian0nSWUrRWih0Mwt3Q2aSaNqZZEwyYt_elHZ1Lpxz7-V8ADxitMCI0xe2QAQRzvgVmGHGcCE45tdghlBVFqSkn7fgLsY9QqQSYjkDbjdaZ72DQxb3BfO0cco7Ha10MPkp2DjA2h5qf4C_VmkPO--SdglO8bRgZExJ_yUonYLD1Cfby6MOsPfZjN8-pCLpMMBBDz4c78GNkX3UDxedg_r9rV59FNvderN63RYjp7wwxhAtJKKiwpx3jEmlqNJ4KSspaFvybLXUVAq17ZIIJBGhpVLElLJjRko6B0_ns2PwP5OOqdnnJi5_bCgSVclLQnFOPZ9TsbNJpkyhGYMdZDg2GDUnnA1rLjjpP6OVaa4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>3079464231</pqid></control><display><type>conference_proceeding</type><title>Opinion mining on Indonesian tourism TikTok video content using fasttext and multilayer long short-term memory</title><source>AIP Journals Complete</source><creator>Ariyus, Dony ; Manongga, Danny ; Sembiring, Irwan</creator><contributor>Adhiyoga, Yohanes Galih ; Ramayanti, Desi ; Abdullah, Ade Gafar ; Septanto, Henri</contributor><creatorcontrib>Ariyus, Dony ; Manongga, Danny ; Sembiring, Irwan ; Adhiyoga, Yohanes Galih ; Ramayanti, Desi ; Abdullah, Ade Gafar ; Septanto, Henri</creatorcontrib><description>Social media analysis is a trending topic among researchers, especially in exploring public opinion. The evolution of web 2.0 technology is a strong reason for turning social media into a digital platform that can easily facilitate various user expressions and opinions through diverse content. Expressions and opinions that emerge through interaction between social media users have great potential to be studied and used in various contexts, including for the government, which aims to understand the thoughts of its citizens regarding newly implemented public policies. Recently, the Government of the Republic of Indonesia established five super-priority tourist destinations through the Ministry of Tourism and Creative Economy (Kemenparekraf) to increase foreign exchange through tourism. These destinations are Lake Toba, Labuan Bajo, Borobudur, Mandalika, and Likupang. However, the policies launched need to be analyzed to support the success of the launched policies. One way is to analyze public opinion to find out how many citizens will recommend the destination. TikTok, one of the most used social media platforms on the market, can be used to investigate public opinion about specific tourist locations. Nowadays, many young travelers use TikTok to express their thoughts and feelings. Due to the non-standard language and the frequent use of slang in daily interactions, extracting opinions on TikTok’s social media data presents specific difficulties. It might be beneficial to utilize a language corpus frequently used to analyze public sentiment more accurately. This study used FastText word embedding combined with the Long Short - Term Memory (LSTM) model with single, double, and triple layers to investigate the public’s opinion of Tiktok social media data. Based on the experiment, using FastText and LSTM with multiple layers provides good performance in developing various system innovations for investigating public opinion, especially on social media data TikTok.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0202656</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Data mining ; Digital media ; Multilayers ; Public opinion ; Public policy ; Sentiment analysis ; Social networks ; Tourism</subject><ispartof>AIP conference proceedings, 2024, Vol.3077 (1)</ispartof><rights>Author(s)</rights><rights>2024 Author(s). Published under an exclusive license by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/acp/article-lookup/doi/10.1063/5.0202656$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>309,310,314,777,781,786,787,791,4498,23911,23912,25121,27905,27906,76133</link.rule.ids></links><search><contributor>Adhiyoga, Yohanes Galih</contributor><contributor>Ramayanti, Desi</contributor><contributor>Abdullah, Ade Gafar</contributor><contributor>Septanto, Henri</contributor><creatorcontrib>Ariyus, Dony</creatorcontrib><creatorcontrib>Manongga, Danny</creatorcontrib><creatorcontrib>Sembiring, Irwan</creatorcontrib><title>Opinion mining on Indonesian tourism TikTok video content using fasttext and multilayer long short-term memory</title><title>AIP conference proceedings</title><description>Social media analysis is a trending topic among researchers, especially in exploring public opinion. The evolution of web 2.0 technology is a strong reason for turning social media into a digital platform that can easily facilitate various user expressions and opinions through diverse content. Expressions and opinions that emerge through interaction between social media users have great potential to be studied and used in various contexts, including for the government, which aims to understand the thoughts of its citizens regarding newly implemented public policies. Recently, the Government of the Republic of Indonesia established five super-priority tourist destinations through the Ministry of Tourism and Creative Economy (Kemenparekraf) to increase foreign exchange through tourism. These destinations are Lake Toba, Labuan Bajo, Borobudur, Mandalika, and Likupang. However, the policies launched need to be analyzed to support the success of the launched policies. One way is to analyze public opinion to find out how many citizens will recommend the destination. TikTok, one of the most used social media platforms on the market, can be used to investigate public opinion about specific tourist locations. Nowadays, many young travelers use TikTok to express their thoughts and feelings. Due to the non-standard language and the frequent use of slang in daily interactions, extracting opinions on TikTok’s social media data presents specific difficulties. It might be beneficial to utilize a language corpus frequently used to analyze public sentiment more accurately. This study used FastText word embedding combined with the Long Short - Term Memory (LSTM) model with single, double, and triple layers to investigate the public’s opinion of Tiktok social media data. Based on the experiment, using FastText and LSTM with multiple layers provides good performance in developing various system innovations for investigating public opinion, especially on social media data TikTok.</description><subject>Data mining</subject><subject>Digital media</subject><subject>Multilayers</subject><subject>Public opinion</subject><subject>Public policy</subject><subject>Sentiment analysis</subject><subject>Social networks</subject><subject>Tourism</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkM1KAzEUhYMoWKsL3yDgTpian0nSWUrRWih0Mwt3Q2aSaNqZZEwyYt_elHZ1Lpxz7-V8ADxitMCI0xe2QAQRzvgVmGHGcCE45tdghlBVFqSkn7fgLsY9QqQSYjkDbjdaZ72DQxb3BfO0cco7Ha10MPkp2DjA2h5qf4C_VmkPO--SdglO8bRgZExJ_yUonYLD1Cfby6MOsPfZjN8-pCLpMMBBDz4c78GNkX3UDxedg_r9rV59FNvderN63RYjp7wwxhAtJKKiwpx3jEmlqNJ4KSspaFvybLXUVAq17ZIIJBGhpVLElLJjRko6B0_ns2PwP5OOqdnnJi5_bCgSVclLQnFOPZ9TsbNJpkyhGYMdZDg2GDUnnA1rLjjpP6OVaa4</recordid><startdate>20240712</startdate><enddate>20240712</enddate><creator>Ariyus, Dony</creator><creator>Manongga, Danny</creator><creator>Sembiring, Irwan</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20240712</creationdate><title>Opinion mining on Indonesian tourism TikTok video content using fasttext and multilayer long short-term memory</title><author>Ariyus, Dony ; Manongga, Danny ; Sembiring, Irwan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p636-fff2e7a0379166c55add3de18a9a73b46a03b3f9d0bb8270a0234dd2f4ac5faa3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Data mining</topic><topic>Digital media</topic><topic>Multilayers</topic><topic>Public opinion</topic><topic>Public policy</topic><topic>Sentiment analysis</topic><topic>Social networks</topic><topic>Tourism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ariyus, Dony</creatorcontrib><creatorcontrib>Manongga, Danny</creatorcontrib><creatorcontrib>Sembiring, Irwan</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ariyus, Dony</au><au>Manongga, Danny</au><au>Sembiring, Irwan</au><au>Adhiyoga, Yohanes Galih</au><au>Ramayanti, Desi</au><au>Abdullah, Ade Gafar</au><au>Septanto, Henri</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Opinion mining on Indonesian tourism TikTok video content using fasttext and multilayer long short-term memory</atitle><btitle>AIP conference proceedings</btitle><date>2024-07-12</date><risdate>2024</risdate><volume>3077</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Social media analysis is a trending topic among researchers, especially in exploring public opinion. The evolution of web 2.0 technology is a strong reason for turning social media into a digital platform that can easily facilitate various user expressions and opinions through diverse content. Expressions and opinions that emerge through interaction between social media users have great potential to be studied and used in various contexts, including for the government, which aims to understand the thoughts of its citizens regarding newly implemented public policies. Recently, the Government of the Republic of Indonesia established five super-priority tourist destinations through the Ministry of Tourism and Creative Economy (Kemenparekraf) to increase foreign exchange through tourism. These destinations are Lake Toba, Labuan Bajo, Borobudur, Mandalika, and Likupang. However, the policies launched need to be analyzed to support the success of the launched policies. One way is to analyze public opinion to find out how many citizens will recommend the destination. TikTok, one of the most used social media platforms on the market, can be used to investigate public opinion about specific tourist locations. Nowadays, many young travelers use TikTok to express their thoughts and feelings. Due to the non-standard language and the frequent use of slang in daily interactions, extracting opinions on TikTok’s social media data presents specific difficulties. It might be beneficial to utilize a language corpus frequently used to analyze public sentiment more accurately. This study used FastText word embedding combined with the Long Short - Term Memory (LSTM) model with single, double, and triple layers to investigate the public’s opinion of Tiktok social media data. Based on the experiment, using FastText and LSTM with multiple layers provides good performance in developing various system innovations for investigating public opinion, especially on social media data TikTok.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0202656</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0094-243X
ispartof AIP conference proceedings, 2024, Vol.3077 (1)
issn 0094-243X
1551-7616
language eng
recordid cdi_proquest_journals_3079464231
source AIP Journals Complete
subjects Data mining
Digital media
Multilayers
Public opinion
Public policy
Sentiment analysis
Social networks
Tourism
title Opinion mining on Indonesian tourism TikTok video content using fasttext and multilayer long short-term memory
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T08%3A23%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Opinion%20mining%20on%20Indonesian%20tourism%20TikTok%20video%20content%20using%20fasttext%20and%20multilayer%20long%20short-term%20memory&rft.btitle=AIP%20conference%20proceedings&rft.au=Ariyus,%20Dony&rft.date=2024-07-12&rft.volume=3077&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/5.0202656&rft_dat=%3Cproquest_scita%3E3079464231%3C/proquest_scita%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3079464231&rft_id=info:pmid/&rfr_iscdi=true