Name
Title | ||
|---|---|---|
How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing Style. |
Abstract | ||
|---|---|---|
Rapid development of Internet technologies promotes traditional newspapers to report news on social networks. However, people on social networks may have different needs which naturally arises the question: whether can we analyze the influence of writing style on news quality automatically and assist writers in improving news quality? Itu0027s challenging due to writing style and u0027qualityu0027 are hard to measure. First, we use u0027popularityu0027 as the measure of u0027qualityu0027. It is natural on social networks but brings new problems: popularity are also influenced by event and publisher. So we design two methods to alleviate their influence. Then, we proposed eight types of linguistic features (53 features in all) according eight writing guidelines and analyze their relationship with news quality. The experimental results show these linguistic features influence greatly on news quality. Based on it, we design a news quality assessment model on social network (SNQAM). SNQAM performs excellently on predicting quality, presenting interpretable quality score and giving accessible suggestions on how to improve it according to writing guidelines we referred to. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Computation and Language | Journal |
Volume | Citations | PageRank |
abs/1902.00750 | 0 | 0.34 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuting Yang | 1 | 44 | 10.79 |
| Juan Cao | 2 | 355 | 30.20 |
| Mingyan Lu | 3 | 0 | 0.34 |
| Jintao Li | 4 | 1488 | 111.30 |
| Chia-Wen Lin | 5 | 1639 | 120.23 |