5 research outputs found
"Chinese Virus” as Anchor for Engaging with COVID-19 Information: Anchoring Bias Leading to Racism and Xenophobia
Information dissemination from official sources coupled with adoption of message by
the public during a pandemic crisis (COVID- 19) are essential components of collective action
aimed at combating virus spread. During the onset of the COVID-19 crisis in the USA,
President Donald Trump referred to the Coronavirus outbreak as a result of a “Chinese virus.”
The president justified his choice of words given that the virus “originated in China.” Although
indeed the virus was reported as originating in Wuhan, China, concerns about the use of the
term and xenophobic/racist feelings emerged as a result. Considering that individuals are
constantly engaging with information about the severe repercussion of the pandemic; social
distancing, constant hand washing, disinfecting surfaces, economic consequences of rapid
spread, increased death toll, and changes in our modus vivendi, for example, labeling the
pandemic might result in anchoring bias. Anchoring bias is a consequence of random and at
times uninformed outset (initial information) influencing perception of subsequent information.
Therefore, when individuals attempt to adjust to new information, features of the anchor (initial
information) to make judgements of new evidence persist. Thus, “Chinese virus” might inform
attitudes towards new information presented on social media. In order to understand
repercussions of labeling the pandemic, data is being collected via Tweet stream about
COVID-19 to understand emotional content of tweets (emotional content analysis). Terms used
to define criteria include “coronavirus,” “corona virus,” “covid-19,” “covid19,” and “Chinese,”
“Chinese-virus.” Additionally, by using location-based tweets, scope was limited to tweets
within the USA
Analysis of Public Perception of Multiple Community Issues through Social Media Mining during a Pandemic
The COVID-19 pandemic affected almost every aspect of our lives. It rapidly changed
the way we behave in our daily lives, including how we seek and access information. Social
media has become pivotal for accessing information about the pandemic, though not all
information available is reliable. Therefore, this study uses a social media mining approach to
analyze the public’s sentiment during COVID-19 pandemic through social media posts (e.g.
Twitter). Social media mining is crucial for understanding information behavior of individuals in
a time when collective action is essential. Data is being collected through tweets streaming using
terms related to coronavirus (“coronavirus” and “covid19”), and limited to tweets within the
USA. Additionally, analysis on the aggregated tweets to understand emotional content of tweets
was conducted alongside visual content (memes) related to the pandemic, which were collected
for content analysis. Text mining and sentiment analysis serve as an avenue for understanding
implicit meaning in social media posts, thus furthering a more complete understanding of
messages transmitted via social media related to COVID-19. The analysis will be correlated with
other aspects, such as timeline and pertinent activities. Understanding the process for collecting
social media data during a world crisis (pandemic), creates a context where social media data can
be analyzed through different perspectives, thus leading to a more in-depth understanding of
efforts at communication about COVID-19 (education strategies, preventive behaviors, etc.), and
the public’s response to the crisis
Komposisi Kimia dan Uji Aktivitas Antibakteri Minyak Atsiri Daun Kayu Putih (Melaleuca Cajuputi) dari Kota Singkawang
Kayu putih (Melaleuca cajuputi) merupakan tumbuhan yang banyak dijumpai di pesisir pantai Kota Singkawang. Tumbuhan ini berpotensi digunakan untuk mengobati diare. Penelitian ini bertujuan untuk mengetahui aktivitas antibakteri daun kayu putih yang berasal dari Kota Singkawang terhadap bakteri uji Escherichia coli dan Staphylococcus aureus. Metode yang digunakan untuk isolasi minyak atsiri yaitu distilasi uap, sedangkan uji aktivitas antibakteri menggunakan metode difusi sumuran. Hasil isolasi minyak atsiri daun kayu putih menghasilkan rendemen sebesar 0,55%. Analisis GC-MS menghasilkan 26 puncak senyawa dengan 2 senyawa utama yaitu 1,8 sineol sebesar 71,96% dan alpha-terpineol sebesar 11,44%. Hasil uji aktivitas antibakteri minyak atsiri daun kayu putih terhadap bakteri E. coli dan S. aureus menghasilkan aktivitas yang tergolong lemah. Diameter zona hambat terhadap bakteri E. coli dengan konsentrasi 50µg/µl menghasilkan zona sebesar 4,39 mm, sedangkan pada bakteri S. aureus yaitu sebesar 4,62 mm