運用模糊分析預測台灣總統選舉

Forecasting President Election in Taiwan by Fuzzy Approach

黃鈺翔(Yu-Shiang Huang)

指導教授 ： 陸海文

崑山科技大學/商業管理學院/企業管理研究所/碩士(2004年)

https://doi.org/10.6828/KSU.2004.00059

摘要

選舉預測的研究中，一般以民意調查資料作為分析的主體，即民調支持度來推估選舉結果。由於選舉民調普遍的報導，民調已被視為政治的工具，媒體、民眾、政黨以及候選人，都會將民調當成指標工具，做為決策的參考。但選戰期間各新聞媒體所報導的民調資訊存在著抽樣誤差及民調本身隨著時間做動態改變的特性，使得選戰期間產生了不精確性與模糊性的民調資訊，若是依據單獨的民調資訊做決策其預測結果堪慮。
因此，本研究以民意調查為資訊，運用層級分析與權重的概念來建構系統化的選舉評估模式，將複雜的選舉問題用系統架構的方式來呈現。將預測總統選舉的系統架構分為三層，各層分別如下：第三層為民調資訊層；第二層為資訊來源層以及第一層為媒體類別層，各層級間均以客觀的資料來計算相對應的權重，使權重能夠反映資訊的現況。如，第三層以時間作為其權重；第二層以各報紙的噫瓛v與電視的收視率為其權重；第一層以民眾看報紙與看電視的相對人數為其權重，來彙整民調的相關資訊為一決策的模糊數。在整合所有民調資訊為一評估的模糊數後採用模糊排序的方式，客觀的評斷出最終的民調結果，判定何者為最可能的當選人。在選舉過程中藉由本模式所整合的資訊，可提供民眾、政黨以及候選人決策之參考。
本研究實証以2004年總統大選民調資訊為例，依本研究模式評估的結果顯示以泛藍為最可能的當選人，但投票結果卻與本研究的預測相違背，其原因可能有下列兩點：（一）民調資訊蒐集的時間點，本研究所蒐集到的民調資訊，是媒體根據選委會規定下公佈至投票前十天，在最後十天的資訊無法取得下，本研究是在法源的規定下，以有限的資訊進行分析，故民調資訊的時間點往往會隨著事件的發生而產生誤差；（二）策略性投票行為及重大事件的衝擊，在越接近投票日選情越激烈，各種選舉狀況皆有可能發生，如本次投票前一天的槍擊事件，對選情產生莫大的影響，如此重大的事件發生是選舉預測中所無法預料。

關鍵字

模糊排序 ； 權重 ； 選舉預測 ； 民調

並列摘要

Research studies about election prediction usually use public opinion surveys as their focus of analysis and draw on findings of support rates to predict election results. Thanks to the prevalent and pervasive reporting of election polls, public opinion polls and surveys have been regarded as a political tool and are often used as an indicator and reference for decision making by the media, the public, political parties and candidates. However, there are many problems of survey measurement, such as random sampling error reported in news stories and late-swing, i.e., people changing their minds after they are surveyed, resulting in confusion and inaccurate information during a campaign period.
This current study makes use of polling data and information to build a systematic model for election assessment by adopting analytical hierarchy process and relative weighting, and complicated issues surrounding elections and voters will be presented in a systematic framework. This present study proposes that the systematic framework for predicting presidential elections should consist of three levels. The first level contains poll information. Sources of information are on the second level and categorization of the media on the third level. Objective data are used to calculate a corresponding weighting for each level so that the weightings may reflect actual situations. For example, by weighting factors such as time on the first level, newspaper reading rates and TV ratings on the second level, and the relative number of people reading newspapers and watching TV on the third level, a fuzzy number can be formulated for decision-making. After integrating all poll information into a fuzzy number for estimation, a fuzzy relation is then established to interpret objectively the final results of poll surveys and thus determine which candidate has the highest support rate and will most likely be elected. This study’s proposed model can be utilized in any campaign period to compile poll information as a reference for decision making by the public, political parties and candidates.
Using polling data from the 2004 Taiwan presidential election, this study’s model predicted that pan-blue candidates would most likely win the election, which, however, contrasted the actual results. This may be attributable to the following two reasons. First, time frame of polling data collection. By law, the results of any public opinion polls, either current or historic, may not be publicized in the last ten days of campaigning according to Taiwan’s Central Election Commission. Second, strategic voting behavior and impact of critical incidents. As election day gets closer, any fierce campaign activity may bring about a big hoopla surrounding the election.

並列關鍵字

Election prediction ； Fuzzy ranking ； Weighting ； Public opinion survey

參考文獻

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