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|pageEditor=Samuel.yemane.ayele | |pageEditor=Samuel.yemane.ayele | ||
|contributionType=1 | |contributionType=1 | ||
| + | |Academic Field=Data Mining | ||
}} | }} | ||
{{Event Series Related Identifier}} | {{Event Series Related Identifier}} | ||
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{{S Event Series}} | {{S Event Series}} | ||
The rapid growth of Internet usage in the last two decades adds new challenges to understand the informal user generated content (UGC) on the Internet. Textual UGC refers to textual posts on social media, blogs, emails, chat conversations, instant messages, forums, reviews, or advertisements that are created by end-users of an online system. A large portion of language used on textual UGC is informal. Informal text is the style of writing that disregard language grammars and uses a mixture of abbreviations and context dependent terms. The straightforward application of state of-the-art Natural Language Processing approaches on informal text typically results in significantly degraded performance due to the following reasons: the lack of sentence structure; the lack of enough context required; the seldom entities involved; the noisy sparse contents of users' contributions; and the untrusted facts contained. It is the aim of this work- shop to bring the attention of researchers to the opportunities and challenges involved in informal text processing. In particular, we are interested in discussing informal text modeling, normalization, mining, and understanding in addition to various application areas in which UGC is involved. | The rapid growth of Internet usage in the last two decades adds new challenges to understand the informal user generated content (UGC) on the Internet. Textual UGC refers to textual posts on social media, blogs, emails, chat conversations, instant messages, forums, reviews, or advertisements that are created by end-users of an online system. A large portion of language used on textual UGC is informal. Informal text is the style of writing that disregard language grammars and uses a mixture of abbreviations and context dependent terms. The straightforward application of state of-the-art Natural Language Processing approaches on informal text typically results in significantly degraded performance due to the following reasons: the lack of sentence structure; the lack of enough context required; the seldom entities involved; the noisy sparse contents of users' contributions; and the untrusted facts contained. It is the aim of this work- shop to bring the attention of researchers to the opportunities and challenges involved in informal text processing. In particular, we are interested in discussing informal text modeling, normalization, mining, and understanding in addition to various application areas in which UGC is involved. | ||
Latest revision as of 14:33, 24 August 2022
The rapid growth of Internet usage in the last two decades adds new challenges to understand the informal user generated content (UGC) on the Internet. Textual UGC refers to textual posts on social media, blogs, emails, chat conversations, instant messages, forums, reviews, or advertisements that are created by end-users of an online system. A large portion of language used on textual UGC is informal. Informal text is the style of writing that disregard language grammars and uses a mixture of abbreviations and context dependent terms. The straightforward application of state of-the-art Natural Language Processing approaches on informal text typically results in significantly degraded performance due to the following reasons: the lack of sentence structure; the lack of enough context required; the seldom entities involved; the noisy sparse contents of users' contributions; and the untrusted facts contained. It is the aim of this work- shop to bring the attention of researchers to the opportunities and challenges involved in informal text processing. In particular, we are interested in discussing informal text modeling, normalization, mining, and understanding in addition to various application areas in which UGC is involved.
