我收到的计数和细分推文

Question

有没有办法计算有多少人发推特给我，并包含一个特定的标签，并按用户分类，例如，

• 用户A使用#certainhashtag向我发送了10次推文
• 用户B使用#certainhashtag 8次向我发送推文

等等

Answer 1

您可以将q参数与https://developer.twitter.com/en/docs/tweets/search/api-reference/get-search-tweets.html一起使用搜索API（@you #certainhashtag）。

所以在这里你有推文提到你并包含你的标签。

您可以将它们写入CSV文件。要在Linux系统上执行计数，您将使用以下几个命令来实现它：awk，cut，grep，wc，uniq ...

或者在获取推文时，您可以编写如下过滤器：

• 如果推文的发件人用户是@you：pass（结果可以返回你的推文）
• 管理每个用户ID的计数器。

Answer 2

您可以使用counts endpoint使用高级搜索API来执行此操作。 30天和完整归档搜索API都支持计费，在付费高级层（在免费沙箱中不可用）。

您将进行类似于此查询的查询，以获取计数数据的时间序列。

{
    "query": "to:andypiper from:userA #certainhashtag",
    "bucket": "day"
}

结果看起来像这样（对于30天的搜索请求）：

{
    "results": [
        {
            "timePeriod": "201809040000",
            "count": 2
        },
        {
            "timePeriod": "201809030000",
            "count": 0
        },
        {
            "timePeriod": "201809020000",
            "count": 0
        },
        {
            "timePeriod": "201809010000",
            "count": 0
        },
        {
            "timePeriod": "201808310000",
            "count": 0
        },
        {
            "timePeriod": "201808300000",
            "count": 0
        },
        {
            "timePeriod": "201808290000",
            "count": 0
        },
        {
            "timePeriod": "201808280000",
            "count": 0
        },
        {
            "timePeriod": "201808270000",
            "count": 0
        },
        {
            "timePeriod": "201808260000",
            "count": 0
        },
        {
            "timePeriod": "201808250000",
            "count": 0
        },
        {
            "timePeriod": "201808240000",
            "count": 0
        },
        {
            "timePeriod": "201808230000",
            "count": 0
        },
        {
            "timePeriod": "201808220000",
            "count": 0
        },
        {
            "timePeriod": "201808210000",
            "count": 0
        },
        {
            "timePeriod": "201808200000",
            "count": 0
        },
        {
            "timePeriod": "201808190000",
            "count": 0
        },
        {
            "timePeriod": "201808180000",
            "count": 0
        },
        {
            "timePeriod": "201808170000",
            "count": 0
        },
        {
            "timePeriod": "201808160000",
            "count": 0
        },
        {
            "timePeriod": "201808150000",
            "count": 0
        },
        {
            "timePeriod": "201808140000",
            "count": 0
        },
        {
            "timePeriod": "201808130000",
            "count": 0
        },
        {
            "timePeriod": "201808120000",
            "count": 0
        },
        {
            "timePeriod": "201808110000",
            "count": 0
        },
        {
            "timePeriod": "201808100000",
            "count": 0
        },
        {
            "timePeriod": "201808090000",
            "count": 0
        },
        {
            "timePeriod": "201808080000",
            "count": 0
        },
        {
            "timePeriod": "201808070000",
            "count": 0
        },
        {
            "timePeriod": "201808060000",
            "count": 0
        },
        {
            "timePeriod": "201808050000",
            "count": 0
        }
    ],
    "totalCount": 2,
    "requestParameters": {
        "bucket": "day",
        "fromDate": "201808050000",
        "toDate": "201809041241"
    }
}

然后你只需要计算总数。