A TIME-SERIES ANALYSIS OF THE DRUG ISSUE, 1985-1990: THE PRESS, THE PRESIDENT AND PUBLIC OPINIO

This study examines the triangular relationship of the press,the president and public opinion about the drug issue in theUnited States from 1985 to 1990. Agenda-setting theory servesas the theoretical foundation for the ARIMA time-series analysis,which attempts to address who is driving the public opinionformation process about drugs: the press, the president, orthe public. The study employs a unique method in that ‘mostimportant problem’ survey results from nine organizationsare quilted into a time-series of 70 monthly points to measurethe public agenda. The press agenda is based on a computerizedcontent analysis of the frequency of coverage of the drug issue,and the presidential agenda is based on a similar analysis ofthe presidents’ public relations agendas. The three univariatetime-series are identified, estimated, and diagnosed. Then thewhite-noise component of each is used in a cross-correlationanalysis to address the research question. The results indicatethat public opinion mirrors or immediately follows the press,though public opinion also drives the press agenda. Second,the study suggests that the president is following the publicagenda, though the president also has strong immediate influenceon public opinion. And, finally it suggests the president mirrorsand follows the media, in addition to following public opinion.The trend of opinion, when viewed in relation to the historyof events surrounding the issue, suggests that the public opinionformation process, as measured through the lens of public opinionpolls, may be a matter of public perceptions of the realityof the issue and of the pseudo-realities of information campaignsand presidential and press attention, which may have their originsback in the heart of the public concern.     

PUBLIC OPINION AND THE TRANSFORMATION OF THE SOVIET UNION

This article examines the relationship between public opinionand the transformation of the Soviet Union. Results of an August1990 survey showed that the majority of adults supported democraticreform, but lacked confidence in the Soviet regime. Young andmiddle-aged people, urban residents, and those with higher educationtended to be more supportive of democratic reform and more alienatedfrom the regime. The nationalities differed widely in supportfor democratic reform and confidence in the regime. In the partlydemocratized political system, Boris Yeltsin acquired a broadfollowing by appealing to the electorate and advocating radicalchange. A February 1991 poll showed that his support was greatestamong Russians who backed the Russian parliament and stronglyendorsed democratic reform and private enterprise. With suchbacking, Yeltsin won the June 1991 Russian presidential electionand then mobilized popular opposition to the August coup attempt.The coup's failure dealt a fatal blow to Communist rule, Gorbachev'sleadership, and the Soviet Union itself.     

Semantic trees for natural language representation

This paper presents a formalism for the representation of complex semantic relations among concepts of natural language. We define a semantic algebra as a set of atomic concepts together with an ordered set of semantic relations. Semantic trees are a graphical representation of a semantic algebra (comparable to Kantorovic trees for boolean or arithmetical expressions). A semantic tree is an ordered tree with nodes labeled with relation and concept names. We generate semantic trees from natural language texts in such a way that they represent the semantic relations which hold among the concepts occurring within that text. This generation process is carried out by a transformational grammar which transforms directly natural language sentences into semantic trees. We present an example for concepts and relations within the domain of computer science where we have generated semantic trees from definition texts by means of a metalanguage for transformational grammars (a sort of metacompiler for transformational grammars). The semantic trees generated so far serve for thesaurus entries in an information retrieval system.