search query: @supervisor Gionis, Aristides / total: 13
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| Author: | Khodier, Mahmoud |
| Title: | Slangsh: a Dictionary of Worldwide Slangs |
| Publication type: | Master's thesis |
| Publication year: | 2016 |
| Pages: | 76 s. + liitt. 10 Language: eng |
| Department/School: | Perustieteiden korkeakoulu |
| Main subject: | Distributed Systems and Services (SCI3045) |
| Supervisor: | Gionis, Aristides |
| Instructor: | Pechenizkiy, Mykola |
| Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201606172603 |
| Location: | P1 Ark Aalto 4222 | Archive |
| Keywords: | slang dictionary crowdsource sentiment analysis and opinion mining collaborative learning knowledge base mutlilingual |
| Abstract (eng): | Currently, people use different online services (i.e., websites and mobile applications) for different language learning purposes. On the hand, online businesses use usually use different approaches and techniques to process a massive amount of text in different languages, in order to analyze users' feedback and opinions regarding different entities such as products, movies, or pictures. Although the available online language learning platforms and opinion mining techniques are useful in different cases, they still suffer from some limitations related to slangs in different languages. Slangs (plural of slang) are any informal words or idioms used by people in different languages and countries. These slangs are continuously developed, especially in dense social networks and communities. In addition, people also use slangs to communicate on online services (e.g., Facebook a ) as well as to write reviews on different websites. Accordingly, learning about specific language's slangs would be useful for many people. The current problems related to slangs are twofold: with people, and with online businesses. For people, there is no any comprehensive online dictionary to learn about worldwide slangs. On the other hand, online businesses have some challenges to understand the semantics (e.g., sentiments and contexts) behind the texts being exchanged on their platforms. Both people and online businesses face the problem of inaccurate translation of slang using current available online translation services. Therefore, in this thesis we propose, design, and develop a novel solution with main objective and vision to build the largest online knowledge base of slangs. In order to achieve this objective, we used different approaches and methodologies both theoretical and empirical. We conducted a literature review in the sentiment analysis domain. In addition, we made different personal interviews as well as an online survey to validate our assumptions and facts about slang development in different languages and countries. Moreover, we followed the action research approach and developed an Android application to evaluate our proposed solution (Slangsh). We found out that Slangsh would have a good potential to build a comprehensive knowledge base of worldwide slang as well as to address the problem of the inaccurate translation of slangs in different languages. The main contribution of this thesis is to design, develop, and propose a novel solution that is based on crowdsourcing and collaborative learning to collect slangs from different languages and countries. |
| ED: | 2016-07-17 |
INSSI record number: 54033
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