小說推廣如何選書？信息流爆款輕松起量

小說推廣想要爆量，單靠野路子的離譜標題是不夠的。小說推廣的本質是內容付費小說信息流推廣，選一本受歡迎的好書才是起量的基礎。

全民自媒體時代，內容創作門檻極低。看多了文章小說，孰優孰劣一眼便知。沖著標題和浮夸情節可能湊個熱鬧小說信息流推廣，真到付費章節，讀者自然不會買單。

思路簡單，以閱文后臺為例，首先拿到后臺所有的書名，然后查詢該書的百度指數。拓展一下可以用主人公去查去小說信息流推廣，也可以查微信指數、微博指數等等。

import requests
import pandas as pd
import index_baidu
def checkw(word):
    cookies=''
    headers = {
        'Connection': 'keep-alive',
        'sec-ch-ua': '^\\^Google',
        'Accept': 'application/json, text/plain, */*',
        'sec-ch-ua-mobile': '?0',
        'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.114 Safari/537.36',
        'index_csrftoken': '',
        'Sec-Fetch-Site': 'same-origin',
        'Sec-Fetch-Mode': 'cors',
        'Sec-Fetch-Dest': 'empty',
        'Referer': 'https://index.baidu.com/v2/main/index.html',
        'Accept-Language': 'zh-CN,zh;q=0.9',
        'Cookie':cookies
    }
    params = (
        ('word', word),
    )
    response = requests.get('https://index.baidu.com/api/AddWordApi/checkWordsExists', headers=headers, params=params)
    #print (response.json())
    return response.json()
def yunwen(page):
    cookies = ''
    headers = {
        'Connection': 'keep-alive',
        'sec-ch-ua': '^\\^Google',
        'Accept': 'application/json, text/plain, */*',
        'sec-ch-ua-mobile': '?0',
        'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.114 Safari/537.36',
        'Sec-Fetch-Site': 'same-origin',
        'Sec-Fetch-Mode': 'cors',
        'Sec-Fetch-Dest': 'empty',
        'Referer': 'https://open.yuewen.com/new/library',
        'Accept-Language': 'zh-CN,zh;q=0.9',
        'cookie':cookies
    }
    params = (
        ('cbid', ''),
        ('page', page),
        ('version', '2'),
        ('category1', '2'),
        ('allwords', '-1'),
        ('category2', '-1'),
        ('isfinish', '-1'),
        ('level', '-1'),
    )
    response = requests.get('https://open.yuewen.com/api/wechatspread/bookSpread', headers=headers, params=params)
    return response.json()
while nextpaget:
    p=p+1
    data=yunwen(p)
    maxpage=data['data']['maxPage']
    datalist+=data['data']['list']
    print (p,maxpage)
    if p>maxpage:
        nextpaget=False
    else:
        pass
df=pd.DataFrame(datalist)
df.to_csv("datalist.csv",encoding="utf_8_sig")
for i in datalist:
    #try:
    #    data=checkw(i['BookName'])
    #    try:
    #        status=data['data']['result'][0]['status']
    #        lastday=""
    #    except:
    #        status="有指數"
    #        words = [[{"name": i['BookName'], "wordType": 1}]]
    #        result=index_baidu.get_index_data(words)
    #        lastday=result[-1]
    #except:
    #    status="失敗"
    #    lastday=""
    try:
        words = [[{"name": i['BookName'], "wordType": 1}]]
        status,avg,day30=index_baidu.get_index_data(words)
    except:
        status,avg,day30="失敗","",""
    i['status']=status
    i['avg']=avg
    i['day30']=",".join(day30)
    returndatalist.append(i)
    print (i['BookName'],status,avg)
df=pd.DataFrame(returndatalist)
df.to_csv("yuewen.csv",encoding="utf_8_sig")

其他想法，歡迎交流！

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