本文關(guān)鍵詞： 話題挖掘 用戶影響力 微博 文本挖掘　出處：《情報(bào)雜志》2017年04期 　論文類型：期刊論文

【摘要】：[目的/意義]對(duì)微博消息進(jìn)行熱點(diǎn)話題挖掘,進(jìn)而從海量微博文本中實(shí)時(shí)找出用戶關(guān)注、討論的熱點(diǎn)事件,是進(jìn)行輿情監(jiān)測(cè)、應(yīng)急管理的基礎(chǔ)。然而,現(xiàn)有微博熱點(diǎn)話題檢測(cè)研究卻大多忽略了不同影響力用戶對(duì)話題產(chǎn)生及傳播的作用,并且檢測(cè)結(jié)果直觀性較差。針對(duì)此問題,提出了基于用戶影響力的熱點(diǎn)話題檢測(cè)方法。[方法/過程]首先識(shí)別用戶特征要素,構(gòu)建用戶影響力模型,計(jì)算用戶影響力;然后,綜合考慮主題詞影響力、影響力增長(zhǎng)速度和增長(zhǎng)斜率,提出基于用戶影響力的微博熱點(diǎn)話題主題詞抽取方法,抽取主題詞簇;之后,識(shí)別核心主題詞并進(jìn)行熱點(diǎn)話題關(guān)鍵詞抽取。最后,通過實(shí)驗(yàn)驗(yàn)證方法的有效性。[結(jié)果/結(jié)論]實(shí)驗(yàn)結(jié)果表明:基于用戶影響力的熱點(diǎn)話題檢測(cè)方法能夠有效識(shí)別并直觀表達(dá)出檢測(cè)時(shí)間窗口內(nèi)的典型熱點(diǎn)話題;該方法能有效提升實(shí)證性熱點(diǎn)話題識(shí)別效率,減少娛樂性熱點(diǎn)話題的識(shí)別;通過對(duì)不同時(shí)間窗口內(nèi)同一話題的關(guān)鍵詞抽取,可以實(shí)現(xiàn)對(duì)相應(yīng)話題的熱點(diǎn)跟蹤。
[Abstract]:[Objective / significance] to mine the hot topic of Weibo message, and then to find out the user's attention and the hot events discussed in real time from the massive Weibo text, which is the basis of public opinion monitoring and emergency management. The existing research on Weibo hot topic detection mostly ignores the influence of different users on the topic generation and dissemination, and the detection results are not intuitive. A hot topic detection method based on user influence is proposed. [Method / process: firstly, the user characteristic elements are identified, the user influence model is constructed, and the user influence is calculated. Then, considering the influence of theme words, the speed of influence growth and the slope of growth, a method of extracting the subject words of Weibo hot topic based on user influence is put forward to extract the cluster of theme words. After that, the key words are identified and the key words of hot topics are extracted. Finally, the effectiveness of the method is verified by experiments. [Results / conclusion] the experimental results show that the hot topic detection method based on user's influence can effectively identify and express the typical hot topic in the detection time window. The method can effectively improve the efficiency of the empirical hot topic identification and reduce the entertainment hot topic recognition. By extracting the keywords of the same topic in different time windows, the hot spot tracking can be realized.
【作者單位】： 大連理工大學(xué)管理與經(jīng)濟(jì)學(xué)部;
【基金】：遼寧省社會(huì)科學(xué)規(guī)劃基金重點(diǎn)項(xiàng)目“突發(fā)事件網(wǎng)絡(luò)輿情的動(dòng)態(tài)監(jiān)測(cè)與預(yù)警策略研究”(編號(hào):L15AGL017) 國(guó)家自然科學(xué)基金項(xiàng)目“在線知識(shí)社區(qū)中社會(huì)系統(tǒng)與知識(shí)系統(tǒng)協(xié)同序化機(jī)制和規(guī)律研究”(編號(hào):71573030)的研究成果之一
【分類號(hào)】：TP393.092;TP391.1
【正文快照】： 關(guān)鍵詞話題挖掘用戶影響力微博文本挖掘引用格式裘江南,谷文靜,翟R，

本文編號(hào)：1489356