Peringkasan Sentimen Esktraktif di Twitter Menggunakan Hybrid TF-IDF dan Cosine Similarity
The using of Twitter by selebrities has become a new trend of impression management strategy. Mining public reaction in social media is a good strategy to obtain feedbacks, but extracting it are not trivial matter. Reads hundred of tweets while determine their sentiment polarity are time consuming....
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| Main Authors: | , |
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| Format: | EJournal Article |
| Published: |
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.,
2016-07-31.
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| Online Access: | Get Fulltext Get Fulltext |
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| LEADER | 02762 am a22003013u 4500 | ||
|---|---|---|---|
| 001 | IJCSS_16625 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Wahid, Devid Haryalesmana |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a SN, Azhari |e author |
| 245 | 0 | 0 | |a Peringkasan Sentimen Esktraktif di Twitter Menggunakan Hybrid TF-IDF dan Cosine Similarity |
| 260 | |b IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., |c 2016-07-31. | ||
| 500 | |a https://jurnal.ugm.ac.id/ijccs/article/view/16625 | ||
| 520 | |a The using of Twitter by selebrities has become a new trend of impression management strategy. Mining public reaction in social media is a good strategy to obtain feedbacks, but extracting it are not trivial matter. Reads hundred of tweets while determine their sentiment polarity are time consuming. Extractive sentiment summarization machine are needed to address this issue. Previous research generally do not include sentiment information contained in a tweet as weight factor, as a results only general topics of discussion are extracted. This research aimed to do an extractive sentiment summarization on both positive and negative sentiment mentioning Indonesian selebrity, Agnes Monica, by combining SentiStrength, Hybrid TF-IDF, and Cosine Similarity. SentiStrength is used to obtain sentiment strength score and classify tweet as a positive, negative or neutral. The summarization of posisitve and negative sentiment can be done by rank tweets using Hybrid TF-IDF summarization and sentiment strength score as additional weight then removing similar tweet by using Cosine Similarity. The test results showed that the combination of SentiStrength, Hybrid TF-IDF, and Cosine Similarity perform better than using Hybrid TF-IDF only, given an average 60% accuracy and 62% f-measure. This is due to the addition of sentiment score as a weight factor in sentiment summarization. | ||
| 540 | |a Copyright (c) 2016 IJCCS - Indonesian Journal of Computing and Cybernetics Systems | ||
| 540 | |a http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Computer Science | ||
| 690 | |a extractive sentiment summarization, sentiment analysist, classification, automatic text summarization, SentiStrength, Hybrid TF-IDF | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 10, No 2 (2016): July; 207-218 | |
| 786 | 0 | |n 2460-7258 | |
| 786 | 0 | |n 1978-1520 | |
| 787 | 0 | |n https://jurnal.ugm.ac.id/ijccs/article/view/16625/11694 | |
| 856 | 4 | 1 | |u https://jurnal.ugm.ac.id/ijccs/article/view/16625 |z Get Fulltext |
| 856 | 4 | 1 | |u https://jurnal.ugm.ac.id/ijccs/article/view/16625/11694 |z Get Fulltext |