زهره هنرجویان

The purpose of this study was to systematically examine dimensions, aspects, and levels of search stopping in the literature in order to identify gaps in the field.

Research reports on the subject published between 1961-2020 were identified in databases. The contents of 60 studies found were thematically analysed in terms of basic, organizing, and comprehensive concepts.

The reviewed studies have identified two stopping levels, namely session-level stopping and query-level/ result- summary- level stopping. At the latter level, the search session does not stop permanently, but the user continues searching after refining the query. The studies also referred to another stopping method labeled as “search- engine- result- page- level stopping” in which the user leaves the result page without clicking on any result after making a general inference of the search results. Then, the user may or may not continue searching after refining the query. Here, we are not dealing with another level of stopping, but only the time of making decision to stop is changed. Most of the 60 studies we identified dealt with session-level stopping. Identifying stopping rules, examining the application of stopping rules in various contexts, identifying the factors affecting search stopping or query stopping, checking search- engine- result- page- level stopping, examining the depth of users' search, distinguishing between stopping due to satisfaction or frustration, and exploring search stopping signs were dimensions of search stopping studied in the literature.  Stopping rules included satisfaction and frustration, magnitude threshold, difference threshold, representational stability, mental list, and single criterion. Also, factors affecting stopping search included time constraints, search task structure, information scent, user interface features, importance of the task to the users, motivation, domain knowledge, interest in the topic, need for closure and need for cognition.

Our review showed that studies each dealt with some specific aspect(s) of search stopping behavior and sought to identify the rules or factors affecting it. Research gaps we identified include not investigating the impact of variables such as search language, task difficulty, and individual differences on stopping behavior, the detailed differentiation of the signs of good abandonment from bad ones, and the use of eye tracking technology and recording electrical activity of the brain (Electroencephalography) to better understand the stopping behavior.

The objective of the present study has been to systematically review semantic research studies on social tagging systems in order to identify the researchers’ areas of interest, to investigate the impact of semantic issues on information retrieval in ​such systems, and to identify research gaps in this area​​.

Ninety-eight studies were found by searching ​ relevant ​databases. After initial investigation and consultation with two specialists in the field, 41 studies published in 2003-2018 were reviewed.

Important topics of semantic research on social tagging systems include producing an automatic semantic tagging algorithm, designing a semantic tagging system, producing an algorithm, extracting hierarchical relationship from a set of tags, and using WordNet to determine semantic relationships among tags. In addition, research gaps identified include devising a method for identifying sources containing a specific meaning of a tag without having to review all sources, exploring the possibility of using clustering methods to cluster sources or users of folksonomies, and designing a semantic tagging system which is user-friendly. All of these issues should be taken into account in future research.

Given the gaps identified, the subject of semantics in tagging systems needs further investigation, as it has a direct impact on search and retrieval by these systems.

In its interactions with the digital environment, Persian language faces a variety of challenges, especially regarding its writing style, which can affect the effectiveness of Persian information retrieval (IR).Persian writers may either ignore some characters or replace them with other ones.

Using a conceptual content analysis method, the present research investigated seven challenging characters to explore the writing behaviors as reflected in the Hamshahri Corpus during 1996-2007. The degree of the writing behavior conformity to the standard Persian writing style was also investigated using "Engagement Index" (i.e. the arithmetic ratio of the words conformed to the standard writing style.

Results showed that the Corpus typists generally tend to omit the challenging characters or replace them with simplified characters. It seems, therefore, that ignoring the challenges in Persian IR systems would not largely affect IR effectiveness. The engagement index equals 0.033 demonstrating the least conformity of the writing behavior to the standard. This may have roots in the fact that Persian writers tend to simplify the writing style due to the “least effort” principle and feel no needs to adhere to the traditional Arabic writing style, as prescribed by the standard.