Abstract: The image of a supplier company is often associated with the well-known
brand it supplies, and its reputation can be influenced by online news circulation. To
maintain a positive image, it is crucial for the company to monitor and manage online
news to rectify any false information. Failure to maintain a good company image can
lead to customer order loss and even company shutdown.
This paper aims to conduct a two-stage sentiment analysis on Indonesian news
articles regarding unilateral layoffs by company XYZ. The first stage will analyze
sentiment in the circulating news about the layoffs, while the second stage will assess
sentiment after the company releases a press release to provide accurate information.
The VADER lexicon-based method, utilizing the InSet and SentiStrength_ID
Indonesian dictionaries, will be employed to analyze sentiment before and after the
press release. This will enable us to compare sentiment and evaluate the effectiveness
of the press release and the Indonesian dictionaries in analyzing sentiment in the
news. The research findings indicate that the company's press release, aimed at
correcting false information, had a positive impact by reducing negative sentiment
and generating a more positive sentiment in the second stage. Moreover, the selection
of the sentiment analysis dictionary also plays a critical role in determining the
sentiment analysis results.
Keywords: InSet, Lexicon, Sentiment, SentiStrength_ID, VADER.