COMPANY:

Japanese-based tractor and heavy equipment manufacturer

A science woman majoring in computer science at the Technical University of Madrid in Spain. Currently studying abroad at Sains University Malaysia. Using machine learning to study Twitter cyber bling. During her internship at a start-up company in Spain, she used Python, MySQL, and ELT for data management. She also has IT skills in UNIX, HTML, JavaScript, Java, C++, etc.

Profile

COUNTRY / REGION

Spain
SEX
Female
UNIVERSITY
Universidad Politécnica de Madrid
SPECIALIZATION
Computer Science
ACADEMIC LEVEL
Bachelor

MESSAGE

I have been learning Japanese since I was in Senior Highschool, and I have always wanted to either study or work in Japan. I tried to get into an exchange program in Japan during my final undergraduate year, however, due to my major, I was unable to do so. Instead, I came to Malaysia for a semester. It has been tough during these past few years, I had to postpone my exchange due to the COVID-19 pandemic and my program almost got canceled. I wanted to find a job in Japan since my experience in Asia so far has been fantastic and I already have learned lots of things about Japan through my language study and reading from different sources.

I came across ASIA to JAPAN’s FAST OFFER International program (previously known as ‘Study Go Work JAPAN’) website when I was looking for fresh grad job opportunities in Japan where they can sponsor your visa. At first, I thought this agency was not aimed at me, since it says ‘Asia’ to Japan and I’m from Spain (Europe). However, one day, I got a message through LinkedIn from them, and they told me that everyone was welcome to give it a try!

After passing a screening interview, I had to prepare all the necessary documents and information, and after that, the matchmaking process with Japanese companies began. I was really excited! Finally, my dream was starting to materialize.

In total, I attended interviews for three companies, and before each interview, I had a couple of mentoring sessions with my tutor, who helped me greatly and gave me useful advice to ace my interviews and get a job in Japan! Since my major is computer engineering, I had to talk about my Final Year Project in every interview and answer technical questions about it. Although I passed the JLPT N2 exam, due to my nervousness I made a few mistakes but the interviewers from all companies were truly kind and understanding, so after my initial insecurity I was able to communicate properly with them and ultimately get an offer!

Due to the COVID-19 situation, all the interviews were held online. Finally, after taking multiple interviews and learning about different companies, I got two offers, and after thinking about them carefully, I accepted the offer from a Japanese-based tractor and heavy equipment manufacturing company!

Most borders have been closed for the past two years, so I could not visit Japan. However, I was lucky enough to be able to spend 4 days in Osaka at the beginning of October to visit the Headquarters and factories of my company, as well as savor a little bit of Japan before moving there! The company is based in Osaka, so I was able to sightsee the city and visit Osaka Castle and Doutonbori Street with my future coworkers! I can’t thank enough the Fast Offer International team for helping me get where I am today, I encourage everyone who has thought about working in Japan to apply!

FINAL YEAR PROJECT

現在、マレーシアのペナンでコンピューターエンジニアリングの学士論文を書いています。8月に提出する予定です。テーマは、ツイッターでのネットいじめを機械学習(MACHINE LEARNING)で自動検出することです。具体的には、検出された後に、ネットいじめの傍観者はどう反応するのかということです。例えば、加害者をサポートするのか、それとも被害者を守るのかについて着目しています。さらに、傍観者の反応はほかの傍観者に影響されるのかどうかについても研究しています。例えば、傍観者(A)の友達(B)が加害者をサポートすれば、傍観者(A)は影響されて、いじめに加担するのかということです。これらのことを明らかにするためには、自然言語処理 (NATURAL LANGUAGE PROCESSING)、機械学習とネットワークの有向グラフを用います。

 これまでの研究は、加害者か被害者に集中していましたが、傍観者と傍観者のネットワークや影響についてのリサーチペーパーは少ないです。オフラインいじめでは、傍観者はほとんどクラスメイトか同僚です。しかし、ネットいじめでは、傍観者の数はきわめて高いのです。それゆえ、新しい研究だと考えられます。自分の研究で傍観者の態度は理解できれば、ネットいじめが減る可能性が高い。

研究をするためのデータは、ツイッターAPIでクロールしました。ネットいじめに関係があるツイートやそのツイートのメタデータ(ツイートのタイムスタンプやオーナーやスレッドのIDなど)を集めて、データセットを作りました。400ツイート以上集めることができました。

現在、研究の結果は、いまだに解明されていません。しかし、いろいろなことをこれまで学ぶことができました。例えば、リサーチのやり方やAPIの使い方などを理解しました。私の研究は成功すれば、ただいま通ってるUSMというペナンにある大学で博士は、一層の研究をします。

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