Name
Abstract | ||
|---|---|---|
We introduce a systematic method to estimate an economic indicator from the Japanese government by analyzing big Japanese blog data. Explanatory variables are monthly word frequencies. We adopt 1352 words in the section of economics and industry of the Nikkei thesaurus for each candidate word to illustrate the economic index. From this large volume of words, our method automatically selects the words which have strong correlation with the economic indicator and resolves some difficulties in statistics such as the spurious correlation and overfitting. As a result, our model reasonably illustrates the real economy index. The announcement of an economic index from government usually has a time lag, while our proposed method can be real time. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/e20110852 | ENTROPY |
Keywords | Field | DocType |
big blog data,economic index,robust variable selection,regression analysis | Economic indicator,Statistics,Big data,Mathematics,Government,Classical economics | Journal |
Volume | Issue | ISSN |
20 | 11 | 1099-4300 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenta Yamada | 1 | 12 | 1.48 |
| Hideki Takayasu | 2 | 7 | 5.61 |
| Misako Takayasu | 3 | 18 | 5.72 |